Fire History of the 

Appalachian Region: 

A REVIEW AND SYNTHESIS

Charles W. Lafon, Adam T. Naito, Henri D. Grissino-Mayer, 

Sally P. Horn, and Thomas A. Waldrop

United States Department of Agriculture

Forest Service

Southern Research Station

General Technical Report SRS-219

January 2017
Authors

Charles W. Lafon is a Professor of Geography and the Assistant Department Head in 

the Department of Geography at Texas A&M University, College Station, TX 77843-

3147; Adam T. Naito is a Postdoctoral Research Associate in the School of Natural 

Resources and the Environment at the University of Arizona, Tucson, AZ 85721; 

Henri D. Grissino-Mayer is a Professor of Geography in the Department of Geography 

at the University of Tennessee, Knoxville, TN 37996-0925; Sally P. Horn is a Professor 

of Geography in the Department of Geography at the University of Tennessee, Knoxville, 

TN 37996-0925; and Thomas A. Waldrop is a Supervisory Research Forester (retired) 

with the U.S. Department of Agriculture, Forest Service, Southern Research Station, 

Clemson, SC 29634-0331.

Cover photo

View to the east from the top of Reddish Knob on the Virginia-West Virginia border, 

George Washington National Forest. In this photo can be seen the oak-pine mosaic that 

is the typical vegetation cover on mountain slopes in the Ridge and Valley province. The 

pine stands are dominated by Table Mountain pine (Pinus pungens) and pitch pine (Pinus 

rigida), some of which have been scarred by fires in the past. These fire-scarred trees are 

a valuable source of information about fire history. The Reddish Knob fire history site 

discussed in this report is located on the slope to the south (right) of the pond in the middle 

ground. The Shenandoah Valley and the Blue Ridge Mountains lie in the background.

Photograph Disclaimer

All photographs are provided courtesy of the authors, unless otherwise noted.

Product Disclaimer

The use of trade or firm names in this publication is for reader information and does not 

imply endorsement by the U.S. Department of Agriculture of any product or service.

January 2017

Southern Research Station

200 W.T. Weaver Blvd.

Asheville, NC 28804

www.srs.fs.usda.gov
Fire History of the 

Appalachian Region:

A REVIEW AND SYNTHESIS

Charles W. Lafon, Adam T. Naito, Henri D. Grissino-Mayer, 

Sally P. Horn, and Thomas A. Waldrop
ii

Abstract

The importance of fire in shaping Appalachian vegetation has become 

increasingly apparent over the last 25 years. This period has seen declines in 

oak (Quercus) and pine (Pinus) forests and other fire-dependent ecosystems, 

which in the near-exclusion of fire are being replaced by fire-sensitive 

mesophytic vegetation. These vegetation changes imply that Appalachian 

vegetation had developed under a history of burning before the fire-exclusion 

era, a possibility that has motivated investigations of Appalachian fire history 

using proxy evidence. Here we synthesize those investigations to obtain an 

up-to-date portrayal of Appalachian fire history. We organize the report by data 

type, beginning with studies of high-resolution data on recent fires to provide 

a context for interpreting the lower-resolution proxy data. Each proxy is 

addressed in a subsequent chapter, beginning with witness trees and continuing 

to fire-scarred trees, stand age structure, and soil and sediment charcoal. Taken 

together, these proxies portray frequent burning in the past. Fires had occurred 

at short intervals (a few years) for centuries before the fire-exclusion era. 

Indeed, burning has played an important ecological role for millennia. Fires 

were especially common and spatially extensive on landscapes with large 

expanses of oak and pine forest, notably in the Ridge and Valley province 

and the Blue Ridge Mountains. Burning favored oak and pine at the expense 

of mesophytic competitors, but fire exclusion has enabled mesophytic plants 

to expand from fire-sheltered sites onto dry slopes that formerly supported 

pyrogenic vegetation. These changes underscore the need to restore firedependent ecosystems.

Keywords: Age structure, Appalachian Mountains, charcoal, fire history, fire 

regime, fire scars, witness trees.
Fire History of the Appalachian Region: A Review and Synthesis

iii

Acknowledgments

We are grateful for the funding of this synthesis report through the Consortium 

of Appalachian Fire Managers and Scientists (CAFMS), which is supported by 

the Joint Fire Science Program (JFSP). We also thank the reviewers, Steven Q. 

Croy and Don Hagan, for their many useful suggestions that helped us improve 

this report. More broadly, we are especially grateful to Steve for all the 

assistance and ideas he has offered us during our years of studying Appalachian 

fire history. The work we report here has also benefitted from conversations, 

collaborations, and encouragement from many others, particularly Rob Klein, 

Helen Mohr, Beth Buchanan, Margit Bucher, Carol Croy, Nelson Lafon, 

and Dave Cairns, and from several current and former students, especially 

Serena Aldrich, Joanne Ballard, Mathew Boehm, Georgina DeWeese, Ian 

Feathers, Will Flatley, Ellen Gass, Alisa Hass, Jennifer Hoss, Lisa LaForest, 

and Chris Underwood. The studies that we and our students have carried out 

on fire history in the Appalachian region have been supported by grants from 

the Joint Fire Science Program (#01C-3-3-09, #06-3- 1- 05), the National 

Science Foundation (#0538420, #0623321, #0822824, #0928508), the Nature 

Conservancy (#VA022205A, #VA022305B), the Great Smoky Mountains 

Conservation Association, and our universities. Funding for this synthesis 

report was provided through agreement #15-JV-11330136-004 between Texas 

A&M University and the USDA Forest Service, Southern Research Station.
iv

Table of Contents

Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii

Acknowledgments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

Chapter 1. Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

What Role Has Fire Played in Appalachian Vegetation Development?. . . . . . . . . . . . . . 1

Organization of This Report. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Context: A Sketch of Appalachian Fire History. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Chapter 2. The Current Appalachian Fire Regime. . . . . . . . . . . . . . . . . . . . . . . . . . 7

Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Controls of the Fire Regime. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Current Appalachian Fire Cycle. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Geographic Variations in Burning Across the Appalachian Region. . . . . . . . . . . . . . . . . 9

Fire Weather and Climate. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Ignition Source and Seasonality. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Topographic Patterns of Fire. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Conclusions and Implications. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Chapter 3. Forest Composition and Fire Before European 

 Settlement as Inferred from Witness Tree Records. . . . . . . . . . . . . . . . . . . . . 17

Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Objectives and Methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Coarse-Scale Inferences Regarding Presettlement Forest Composition. . . . . . . . . . . . 20

Local Influences of Anthropogenic Activities on Forest Composition 

 and Fire Activity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

Conclusions and Implications. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

Fire History of the Appalachian Region: A Review and Synthesis
Fire History of the Appalachian Region: A Review and Synthesis

v

Table of Contents, cont.

Chapter 4. Appalachian Fire History as Reconstructed from 

 Fire-Scarred Trees. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Field Sampling for Fire History. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Processing Samples and Dating Fire Scars. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Developing a Fire History. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Fire Intervals Reconstructed for the Appalachian Region. . . . . . . . . . . . . . . . . . . . . . . 32

Variability in Fire Intervals. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Temporal Changes in Fire Frequency. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

Fire–Climate Relations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

Ignition Source: People or Lightning?. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

Spatial Patterns of Fire. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

Conclusions and Implications. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

Chapter 5. Stand Age Structure and What It Indicates about Past 

 Fire Regimes and Fire Effects on Vegetation. . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

Field and Laboratory Methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

Synthesis of Age Structure Analyses in the Appalachian Region. . . . . . . . . . . . . . . . . 60

Conclusions and Implications. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

Chapter 6. Appalachian Fire History as Reconstructed from Charcoal. . . 69

Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

Sediment Charcoal Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

Soil Charcoal Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

Charcoal-Based Fire History Research in the Appalachian Region. . . . . . . . . . . . . . . . 76

Conclusions and Implications. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88

Chapter 7. Summary: The Picture That Emerges of Appalachian 

 Fire History. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

Fire History of the Appalachian Region: A Review and Synthesis

1

Chapter 1.

Introduction

WHAT ROLE HAS FIRE PLAYED IN 

APPALACHIAN VEGETATION DEVELOPMENT?

The last 25 years have witnessed a surge of scientific interest in 

Appalachian fire history. Much of this attention can be traced to 

concerns over the declining abundance of important ecosystems, 

especially the widespread and ecologically important oak 

(Quercus)- and pine (Pinus)-dominated forests (e.g., Brose and 

others 2014, Nowacki and Abrams 2008, Williams 1998). These 

forests are dominated by trees with fire adaptations such as thick 

bark, extensive hypogeal roots, rot resistance, and serotinous 

cones: traits that enable the trees to withstand fire or recolonize 

soon after a burn. The abundance of overstory trees with 

these traits suggests that the forests developed under a history 

of burning.

Fires sometimes occur today but not at their former frequency or 

scale because prevention and active suppression have curtailed 

their ignition and spread. The absence of fire appears to be 

favoring a regional shift in vegetation toward maples (Acer spp.) 

and other mesophytic taxa that are not well adapted to recurrent 

fires, especially at short intervals (Nowacki and Abrams 2008). In 

light of this broad vegetation shift, it has been hypothesized that 

fires were a common disturbance before the advent of effective 

fire prevention and suppression (e.g., Abrams 1992, Brose and 

others 2001, Lorimer and others 1994, Williams 1998). To assess 

this hypothesis, researchers have collected evidence about past 

burning from several proxy sources, notably witness trees used 

in original land surveys, fire scars that formed on trees injured 

by fire, establishment dates of trees in the stands containing 

fire-scarred trees, and charcoal that has accumulated in soil 

and sediments. 

Nearly all this research has been conducted within the last 25 

years, and most of it within about the past decade. A literature 

review published in 1990 (Runkle 1990) suggested that at that 

time, fires and other broad-extent disturbances were understood 

to have largely been confined to the peripheries of eastern North 

America’s temperate forest region: places such as the pine 

woods along the Gulf and Atlantic Coastal Plains and the forests’ 

western margins along the prairie border. Nearly all studies of 

disturbance in the core of the region—including Appalachia—

had been focused on small treefall gaps. Recently, however, a 

different picture has begun to emerge, one in which fire played a 

prominent role in vegetation development before the era of fire 

prevention and suppression.

In this report, we review and synthesize the research on fire 

history to characterize what is known today about fire in the 

central and southern Appalachian region and how burning has 

varied over time. We include fire history research from the 

Appalachian Plateau, the Ridge and Valley province, the Blue 

Ridge Mountains, and the Piedmont (fig. 1.01). The Appalachian 

Plateau makes up the western part of the Appalachian highlands. 

It is a region underlain by almost horizontal sedimentary rock 

layers of Paleozoic age, although in some areas the layers have 

been deformed (Shankman and James 2002). The bedrock has 

been dissected, producing rugged terrain of modest elevation 

in most places. The plateau is covered primarily with mixed 

mesophytic forest, which transitions into northern hardwood 

forest in northern Pennsylvania and New York. Northern 

hardwood and red spruce (Picea rubens) forests also extend 

southward into the high elevations along the eastern edge of the 

plateau in West Virginia, where elevations reach 4,800 feet.

The Ridge and Valley province lies to the east of the Appalachian 

Plateau. It is a mountainous region where long, parallel valleys 

have been eroded into folded and faulted sedimentary bedrock 

of Paleozoic age (Shankman and James 2002). The valleys 

alternate with ridges that attain elevations as high as 4,700 feet 

in western Virginia. These ridges are covered primarily with oakdominated forest, although composition varies with topography 

and elevation, resulting in a complex mosaic of oak-dominated 
Fire-scar studies

Sediment charcoal studies

Soil charcoal studies

Witness tree studies

Physiographic province

Appalachian Plateau

Ridge and Valley

Blue Ridge

Piedmont

2 Chapter 1. Introduction

Figure 1.01—Location of study sites in published studies from which data were mined and/or synthesized for 

this report. Purple polygons denote study areas for witness tree records. Orange circles indicate the locations 

of fire-scar study sites. Teal and yellow squares show locations of sediment and soil charcoal samples, 

respectively. The four physiographic provinces of the Appalachian region are indicated in blue-gray.

stands alternating with pine-dominated stands on the driest sites 

and mesophytic stands in moist coves and high elevations. The 

eastern section of the Ridge and Valley province consists of the 

Great Valley, the widest valley in the province.

The Blue Ridge Mountains rise above the Great Valley and form 

the eastern ramparts of the Appalachian Mountains. The Blue 

Ridge bedrock is primarily metamorphic rock of Precambrian and 

Paleozoic age (Shankman and James 2002). North of Roanoke, 

VA, the Blue Ridge province is quite narrow (only 9–12 miles 

in width in places), but it broadens southward toward North 

Carolina and Tennessee, where it contains numerous high ranges 

that attain elevations of nearly 6,700 feet. The Blue Ridge 

Mountains are covered primarily with oak-dominated forest but 

with topographic and elevational variations resembling those of 

the Ridge and Valley province. In general, however, mesophytic 

forests have a greater extent in the Blue Ridge Mountains than in 

the Ridge and Valley province, and the high elevations permit the 

existence of extensive stands of northern hardwoods and sprucefir (Picea-Abies).
Fire History of the Appalachian Region: A Review and Synthesis 3

The Piedmont province is a hilly region of fairly low elevation 

(mostly less than about 1,000–1,500 feet) situated between 

the Blue Ridge Mountains and the Atlantic Coastal Plain. The 

Piedmont is underlain by metamorphic and igneous bedrock of 

Precambrian age (Shankman and James 2002). The forests of this 

region are dominated by a mix of oaks and other hardwoods, as 

well as pines.

The mountainous core of the region—the Ridge and Valley 

province and the Blue Ridge Mountains—has been the primary 

focus for fire history researchers. These areas contain the highest 

relief and the largest concentration of public lands in the Eastern 

United States and therefore provide considerable opportunities 

for restoring fire-favored vegetation. As for the Piedmont, it is 

often not considered part of the Appalachian region, but it is 

linked to the Appalachian Mountains—geologically, ecologically, 

and culturally—and by including it here, we are able to report fire 

history information from a few additional studies.

ORGANIZATION OF THIS REPORT

To contextualize what has been learned from the various fire 

history datasets that we discuss in this report, we begin in this 

introductory chapter by sketching a general history of human fire 

use and how this burning appears to have affected Appalachian 

vegetation. Although lightning ignites some fires in the region 

(Lafon and others 2005, Lynch and Hessl 2010), anthropogenic 

ignitions are more common at present and are thought by most 

researchers to have played the dominant role in the past as well 

(e.g., Aldrich and others 2014, Hessl and others 2011). The 

human control over fire is also exemplified by the near absence 

of fire during the exclusion era. Therefore, conceptual models 

of Appalachian fire and vegetation history align strongly with 

human land use episodes. These conceptual models provide a 

framework for situating the fire history studies to be synthesized 

in subsequent chapters.

In chapter 2, we begin our deeper exploration with the best 

understood period of fire history, the most recent few decades 

within the fire-exclusion era. Fires cannot be entirely excluded, 

and a sufficient number of fires occurs today to permit us to detail 

the present fire regime—the typical patterns of fire frequency, 

extent, seasonality, and severity, and the relationships between 

fire and climate. This knowledge will help us interpret the proxy 

records of past fire regimes.

In chapter 3, we focus on the evidence provided by witness trees, 

which offer a glimpse of tree species distribution at the time of 

European settlement. These records can help determine whether 

fire-dependent trees, such as pine and oak, were widespread 

before European settlement. Although such vegetation patterns do 

not provide direct evidence of past fires, they afford an indirect 

assessment by showing the extent of fire-dependent tree species.

Chapter 4 addresses the direct evidence of fire history provided 

by tree-ring dating of fire scars on trees that were wounded 

by fires but subsequently healed. Dated fire scars offer the 

most detailed records available of fire history over the last 

few centuries. Researchers use the scars and tree rings in 

sections from fire-scarred trees to estimate fire interval, fire 

seasonality, and fire-climate relationships. Fire-scarred trees 

also provide some evidence about the spread of fire over 

Appalachian landscapes.

Additionally, tree-ring dating is used to estimate forest age 

structure, the topic of chapter 5. By characterizing age structure, 

researchers gain insights into past fire severity and learn how 

vegetation responded when the fire regime was altered, for 

example, during the era of fire exclusion.

Obtaining a longer record of past fires requires the analysis of 

charcoal in soils or sediments, the topic of chapter 6. Charcoal 

fragments can be quantified and directly or indirectly dated by 

using radiocarbon analyses to estimate the level of fire activity 

over several centuries to millennia, albeit at a coarser temporal 

and spatial resolution than data from fire-scarred trees. Further, 

pollen grains recovered from sediment cores reveal the broad 

vegetation changes that coincided with variations in fire activity.

Chapter 7 offers conclusions based on these records. Taken 

together, the various lines of evidence, although differing in 

resolution and extent, demonstrate that fire played a crucial role 

on Appalachian landscapes for several centuries to millennia until 

the abrupt decline in fire activity during the exclusion era.

CONTEXT: A SKETCH OF 

APPALACHIAN FIRE HISTORY

The Past Century

A hundred years ago, forests were being logged in every corner 

of Appalachia (Ayres and Ashe 1905, Clarkson 1964), and fires 

burned widely through the cutover lands, threatening forest 

recovery. Logging technologies had developed rapidly with 

industrialization, beginning in the Northeast, where the timber 

was largely exhausted by about 1860 (Williams 1989). Industrial 

logging then spread to the Great Lakes region, accelerating as 

new technologies emerged, and by 1900 the Great Lakes timber 

was depleted. From there logging moved to the South, including 

the southern Appalachian Mountains, where it peaked in 1909 

and was virtually complete by 1930 (Williams 1989).

The logging operations left slash strewn over the landscape, 

providing fuel for catastrophic wildfires (Clarkson 1964, Lafon 

2010). Ignition sources were abundant. Lightning undoubtedly 

ignited some fires, but most were apparently set by humans. 

Log trains threw out sparks, and local residents fired the cutover 
1500

1540

1580

1620

1660

1700

1740

17801820

1860

1900

1940

1980

2020

Fire frequency

Year

4 Chapter 1. Introduction

Figure 1.02—Conceptual model of Appalachian fire history, after Brose 

and others (2001). According to this model, fires occurred regularly during 

aboriginal habitation and European settlement before spiking in frequency 

during the industrial logging episode of the late 1800s. The spike was 

followed by a rapid decline in fire frequency during the fire exclusion era 

that began in the early to mid 1900s.

lands to promote pasture grasses and blueberry production, or 

to reduce populations of snakes, ticks, and chiggers. Concerned 

that forests would fail to regenerate under the incessant burning, 

the Forest Service, U.S. Department of Agriculture, and State 

foresters sought to deter fire through a campaign of prevention 

and suppression (Pyne 1982, Sarvis 1993). These efforts often 

provoked local resistance, including incendiarism, but wildfire 

detection and suppression were largely succeeding by the early 

to middle 20th century. Through labor- and capital-intensive 

campaigns against wildfire, the incidence of fire plummeted. 

Forest vegetation rebounded in Appalachia and throughout 

eastern North America, and today the region contains the largest 

area of temperate forest remaining on Earth.

The foregoing synopsis of fire history is well understood 

qualitatively. Quantitative characterizations of the fire regime 

during the industrial logging period are not widely available, but 

old silvicultural reports provide some indications. For example, 

in assessing the potential for a system of Appalachian forest 

reserves (later, national forests) in the southern Blue Ridge 

Mountains, Ayres and Ashe (1905) traveled the roads and trails 

across an area of 10,000 square miles taking notes, measuring 

timber, and mapping forest extent and timber condition in every 

stream basin. Fire was an important focus of their attention. 

Frequent surface fires had killed tree seedlings and saplings 

on about 80 percent of the land area. Springtime burning was 

practiced so regularly in some watersheds that fires occurred at 

intervals of only 1 or 2 years.

The heavy and widespread burning that occurred around the 

turn of the 20th century undoubtedly favored plant species that 

are well adapted to resist fire or to reproduce in the aftermath 

of fire. Among trees, the Appalachian endemic Table Mountain 

pine (Pinus pungens) and the commonly associated pitch pine 

(P. rigida) are the best suited to such a fire regime. Both species 

have thick bark and resinous wood that resists rot when injured 

by fire (Williams 1998). Table Mountain pine typically bears 

serotinous cones. At present, forest stands dominated by one or 

both species are common as small patches—generally only a few 

acres in extent—within a hardwood forest matrix. The pine stands 

usually occupy dry south- or west-facing mountain slopes and 

ridges, where fire and poor soils likely created an environment 

that thwarted the establishment of most hardwood tree species.

The existence of these pines and other fire-adapted species 

implies a long history of burning in the Appalachian region, 

but the extent of such vegetation before the industrial logging 

phase is not well known. According to a conceptual model of 

Table Mountain pine–pitch pine stands developed by Williams 

(1998), the stands were largely restricted to rock outcrops and 

other xeric sites before European settlement and under the sparse 

human populations of early settlement. As settlements then 

crept into marginal farm lands in more remote valleys, burning 

increased on the adjacent mountainsides, and the pine stands 

gradually expanded. Yet according to Williams’ model, it was 

the logging episode that enabled pine forests to expand widely 

across deforested mountain slopes. Today, the pine stands are 

shrinking. Most have been heavily encroached by hardwood 

shrubs, primarily mountain laurel (Kalmia latifolia); by oaks, 

especially chestnut oak (Quercus montana); and by red maple 

(Acer rubrum), blackgum (Nyssa sylvatica), white pine (Pinus 

strobus), and a few other tree species.

Williams’ (1998) model of the dynamics of Table Mountain 

pine and pitch pine stands can be viewed as a hypothesis about 

fire history, i.e., that fire activity increased over the course of 

settlement, peaked during industrial logging, and plummeted as 

fire prevention and suppression gained success. Indeed, a similar 

conceptual model was published by Brose and others (2001) 

with specific reference to the Appalachian oak forests (fig. 1.02). 

Because the dominant Appalachian oaks thrive under periodic 

surface fires, Brose and others estimated that fires occurred 

regularly, typically at intervals of perhaps a decade, under 

aboriginal habitation and throughout White settlement until the 

latter half of the 19th century. This long period of regular burning 

was followed by a spike in fire frequency and severity during 

the logging episode. Fire activity subsequently declined under 

fire exclusion.

Was Fire Common Before the Logging Episode?

At the time the foregoing models were developed, only the 

last two fire history episodes in each were understood with 

any certainty—fires were known to have been common during 

industrial logging and to have become much less common under 

the fire exclusion that followed. The fire regimes before the 
Fire History of the Appalachian Region: A Review and Synthesis 5

logging episode differ in the two models. The Brose and others 

(2001) model proposes frequent and fairly steady burning for 

at least the last few centuries. The Williams (1998) model, in 

contrast, suggests that fire activity was limited before European 

settlement and did not increase until White populations had risen 

and expanded their influence in the middle to late 19th century. 

Which, if either, model is correct?

Aboriginal Burning Before European Settlement

Resource managers and scientists alike have focused considerable 

attention on the “presettlement” fire regime of the Eastern United 

States (e.g., Brown 2000, Day 1953, Frost 1998, Russell 1983). 

What was the role of fire before European settlement? Did Native 

Americans burn frequently across much of the region, or was 

their influence limited to the vicinity of their villages? How 

broadly did they affect plant distributions? This presettlement 

emphasis reflects a management goal of restoring the landscape 

states that existed before European settlers had altered them. It 

also links to the concept of climax (Clements 1936), the natural 

vegetation that would develop under a particular climate in the 

absence of disturbance. The climax concept dominated ecological 

thought and management practice over much of the 20th century, 

but once fires and other disturbances had been recognized as 

common events on presettlement landscapes, a strict climax 

interpretation was precluded. Nonetheless, presettlement burning 

and its influence on the vegetation have continued to attract 

much interest.

The vegetation, fire regimes, and human cultures that were 

encountered by the first European visitors to North America 

had developed over the Holocene, the geological epoch and 

interglacial period in which we live, which began 11,700 years 

ago. During the previous Pleistocene Epoch, large ice sheets 

had repeatedly covered much of the continent, and the major 

biomes of eastern North America had shifted generally southward 

and downslope under cool glacial climates, with migration 

reversing during warmer interglacial periods (Graham 1999). 

The last continental ice sheet to cover North America reached 

its maximum extent during the last glacial maximum between 

26,500 and 19,000 years ago (Clark and others 2009). At this 

time, ice covered the northern Appalachian region as far south 

as northern Pennsylvania and Ohio, and boreal forest dominated 

by spruce (Picea), fir (Abies), and jack pine (Pinus banksiana) 

prevailed over much of the Appalachian region (Graham 1999). 

The Holocene saw a dramatic rise in temperature. The ice sheet 

melted and vegetation shifted northward and upslope. Boreal 

relicts became confined to the high peaks of the Appalachian 

Mountains, and temperate broadleaf forests came to dominate 

most of the region.

Human impacts on the land intensified through the Holocene. 

During the late Pleistocene and early Holocene, hunter-gatherers 

lived in small, nomadic family groups (Delcourt and Delcourt 

2004, Kehoe 1981). These people may have exerted strong 

influences on their environment, despite sparse populations and 

primitive technology, possibly driving mammoths and other large 

mammals to extinction. By roughly 9,500 years ago, people with 

more sophisticated social organization and localized cultures had 

emerged, marking the beginning of the Archaic archaeological 

period (Delcourt and others 1986). Human influences on 

vegetation likely increased during the late Archaic, with the 

domestication of plants such as sunflower (Helianthus annuus), 

goosefoot (Chenopodium berlandeieri), squash (Cucurbita pepo), 

and marshelder (Iva annua var. macrocarpa), and as Native 

Americans transitioned from foragers to farmers (Delcourt and 

Delcourt 2004, Smith 1989). Fire was used for cooking, warmth, 

and driving game (Delcourt and Delcourt 1997), and forest fires 

set purposefully or by accident likely promoted oak, chestnut 

(Castanea dentata), and pine.

During the Woodland Period (2,800–1,000 years ago), Native 

Americans in North America developed agriculture, pottery, 

textiles, and trade networks (Delcourt and others 1986). 

Their populations were likely concentrated, and burning and 

agricultural activities occurred in close proximity to dwellings 

(Anderson 2001, Chapman and others 1982, Cridlebaugh 1984, 

Delcourt and others 1998, Kneller and Peteet 1993). Maize (Zea 

mays) arrived from Mesoamerica (Smith and Yarnell 2009) and 

became a critical crop by the middle and late Woodland Period 

(Munoz and others 2010).

More sedentary lifestyles and permanent settlements emerged 

in the Appalachian region during the Mississippian Period 

(1,000–300 years ago), when temple mounds and large, protected 

villages were constructed (Blitz 1999, Delcourt and others 1986, 

Schroeder 1999). Agricultural activities were intensive and 

widespread through the region (Cridlebaugh 1984, Delcourt and 

others 1986, Fritz 1990), with maize constituting a significant 

portion of the diet and holding ritual significance (Schroeder 

1999). Farming necessitated the use of fire for clearing the land, 

particularly near settlements, and promoted the development 

of open landscapes (Cridlebaugh 1984, Delcourt and Delcourt 

1998, Delcourt and others 1986) and forest dominance by oak, 

chestnut, and pine (Delcourt and Delcourt 1998). Compilations 

of eyewitness accounts made by early European travelers suggest 

that landscapes of eastern North America had many small prairie 

openings and some extensive grasslands (Bartram 1794, Rostlund 

1957), which were maintained in part by fire. The high diversity 

of endemic grassland species in the Southeastern United States 

suggests that they are natural features that were originally 

maintained by lightning-ignited fires (Noss 2012); however, they 

likely expanded under aboriginal burning.

The role of Native Americans in structuring their environments 

through fire and other technologies has been widely debated. 

Many writers and scholars have argued that Native Americans 

minimally altered their environment and that forests of eastern 

North America existed in largely primeval condition before 
6 Chapter 1. Introduction

Europeans appeared (e.g., Bakeless 1950, Clements 1936). 

Others (e.g., Denevan 1992, Rostlund 1957) have proposed 

that Native Americans had thoroughly humanized the continent 

before European arrival, with fire as the means through which 

their impact was extended beyond the immediate environs of 

their settlements. But how often or how widely these fires might 

have burned is largely a matter of conjecture. Heavy impacts may 

have been concentrated around the most densely populated sites, 

leaving large areas of uninhabited mountainous terrain virtually 

untouched (e.g., Matlack 2013, Williams 1998; cf. Allen 2002).

What is clear is that the aboriginal impact declined after 

European contact, which ushered in the Historic Period (300 

years ago until present) and brought disease, war, and social 

disruption that led to the collapse of native populations (Denevan 

1992, Egloff and Woodward 2006, McEwan and others 2011). 

Depopulation was not necessarily followed immediately by 

European settlement. Some areas of Appalachia and the Eastern 

United States probably remained unoccupied for many decades 

or even a century or more in advance of  White settlement. 

Consequently, some researchers have proposed that these early 

settlers encountered landscapes where fire was less frequent and 

vegetation more “pristine” than it had been a century earlier (e.g., 

Denevan 1992).

Fire History During and After European Settlement

White settlement began at different times in different areas 

of Appalachia. The lower (northern) Shenandoah Valley, for 

example, saw settlement in the early 18th century (Meinig 

1986, Mitchell 1972), but for much of the region beyond the 

major valleys, settlement did not begin until around 1800, and 

marginal lands on mountainous terrain were never populated 

to any large extent. Even fairly remote areas were probably 

touched by anthropogenic fires, however, at least on occasion. 

Many Appalachian settlers were of rural English or Scotch-Irish 

descent, a background that included a heritage of burning to 

facilitate hunting and open-range livestock herding (Johnson and 

Hale 2002). These burning traditions were perpetuated in the 

New World, with the result that a culture of extensive burning 

emerged in Appalachia and the South.

This woods-burning tradition remained intact as populations 

rose and as the wave of industrial logging and mining spilled 

across the region in the late 19th century (Pyne 1982). Logging 

would have facilitated traditional land uses, especially livestock 

herding, by opening the forest and promoting the growth of 

forage and berries. Therefore, many of the fires that coincided 

with the industrial logging epoch were probably ignited by local 

herdsmen, not necessarily by the loggers or log trains. This 

burning continued after the wave of logging had passed. By 

inhibiting forest regeneration, the wildfires became a powerful 

motivator for fire prevention and suppression during the early 

20th century.

Fast forward to the present, and we find that fire exclusion has 

been more successful than early foresters might have expected 

a century ago. But this success has its drawbacks, as recognized 

by many researchers and resource managers. Forest density 

and canopy closure have increased to the point that fire-favored 

trees, especially oaks and pines, are failing to reproduce and are 

being replaced (Lorimer and others 1994, Nowacki and Abrams 

2008, Williams 1998). These genera are important for wildlife 

habitat, timber, and aesthetics, and as the canopy dominants die, 

they are being replaced by mesophytic species such as red maple 

that have colonized the shaded forest understory in the absence 

of fire. Other desirable plants, such as blueberries (Vaccinium

spp.), have also waned while thickets of mountain laurel and 

rhododendron (Rhododendron spp.) have expanded. Such 

changes have prompted a considerable amount of recent research 

on fire ecology and fire history, and have motivated resource 

managers to implement prescribed burns to attempt to restore 

fire-dependent ecosystems.

Purpose of This Report

The present situation calls for a synthesis of the various strands 

of Appalachian fire history research to consolidate recent gains 

in knowledge and to ensure that resource managers have ready 

access to this knowledge. These needs provide the underlying 

motivation for our synthesis report. Most fundamentally, 

the report addresses the history and geography of fire in the 

Appalachian region to elucidate the role that fire has played 

in shaping Appalachian ecosystems. The report is particularly 

concerned with understanding the importance of fire before the 

exclusion era. Were fires common in the past? If so, were they 

primarily limited to the industrial logging episode, or did they 

occur frequently for a longer time? These overarching questions 

link to additional topics, such as the relationship of fire to 

climate, the role of anthropogenic versus lightning ignitions, and 

the vegetation shifts that have accompanied changes in the fire 

regime. By tackling these questions, we intend to provide insights 

that will benefit researchers, managers, and anyone else with an 

interest in the role of fire on Appalachian landscapes.
Figure 2.01—The fire triangle. All three components 

(i.e., oxygen, heat, and fuel) of the triangle must be present 

for fire to occur.

Fire History of the Appalachian Region: A Review and Synthesis

7

INTRODUCTION

We begin our examination of Appalachian fire history by 

characterizing the current fire regime. This is the regime of fire 

exclusion. Although this report focuses on evidence about the 

history of fires before the exclusion era, we begin with the current 

fire regime because of the availability of certain data that cannot 

be obtained from fire scars or other proxy records of fires that 

occurred before the exclusion era. The exclusion-era data provide 

a number of details—e.g., size of burn, date of fire, cause of 

ignition—that improve our ability to interpret the proxy records 

of earlier fires.

Fire incidence data are routinely collected for the lands managed 

by the Forest Service, National Park Service, and other land 

management agencies. Even though fires occur less commonly 

today than in the past, this exclusion-era record of fire permits 

answers to questions that are difficult or impossible to address 

using proxy data. For example, are fires associated with particular 

climatic or weather conditions? Do fires burn preferentially 

in certain types of terrain? Do spatial patterns of human- or 

lightning-ignited fires emerge across the Appalachian region? If 

so, are they related to any specific physical or cultural features?

Exploring such questions will establish a context for interpreting 

the proxy records of earlier fire regimes. For example, the firescar data to be discussed in chapter 4 indicate that past fires 

occurred mostly during the “dormant season” when trees were 

not growing new wood. This dormant period would include part 

or all of fall, winter, and spring. The probable timing of scar 

formation within the broader dormant season can be narrowed 

down through comparisons with the current fire regime, which 

shows predictable relationships with the seasonal cycles of 

weather and plant phenology. These cycles were probably similar 

in the past, and therefore the knowledge gained from the current 

fire regime helps us account for the seasonality of fire scars 

formed in previous centuries.

CONTROLS OF THE FIRE REGIME

For fire to ignite requires the interaction of three elements—

fuel, oxygen, and heat—that are represented in the fire triangle 

(Parisien and Moritz 2009) (fig. 2.01). Fire occurs when the three 

elements are present at the proper levels to initiate combustion. 

Once begun, combustion can proceed until one or more of the 

three elements is removed. A fire regime reflects the degree to 

which the elements of the fire triangle are present on a landscape 

and whether those elements vary over space and time. Thus, 

for example, the conceptual models of Appalachian fire history 

(Brose and others 2001, Williams 1998) shown in the previous 

chapter imply that one or more of the elements has been changed 

by people over time. In fact, people have affected both the fuel 

and heat components of the fire triangle. They have altered the 

vegetation—fuel—in numerous ways that have at times promoted 

fire and at other times discouraged it. They have also ignited fires 

at some places and times and have sought to prevent ignitions at 

others. Additionally, they have applied water or other retardants 

to reduce the temperature of fires and bring them under control. 

The various combinations of these activities have contributed to 

the fire-regime changes proposed in the conceptual models.

Chapter 2. 

The Current Appalachian 

Fire Regime
8 Chapter 2. The Current Appalachian Fire Regime

Humans are not the only control over the elements of the fire 

triangle, however. The natural features of a landscape—its 

climate, terrain, and vegetation—also determine the levels at 

which the elements are present and how they vary spatially 

and temporally (Parisien and Moritz 2009). Consequently, fire 

regimes are related in consistent ways to the natural features 

of the Earth’s surface. Three generalizations seem particularly 

important. First, places with moderately wet climates have 

greater fire activity than places that are extremely wet or dry 

(Meyn and others 2007, Parisien and Moritz 2009, Sauer 1950). 

Moderately wet environments—e.g., temperate and tropical 

grasslands and Mediterranean shrublands—receive enough 

precipitation to support continuous vegetation cover and fairly 

heavy fuel production. Dry climates, in contrast, typically support 

too little vegetation to fuel a fire, whereas in wet climates the 

vegetation usually remains too wet to burn.

Second, in any given environment, fire activity fluctuates over 

time with variations in weather and climate (Lafon and Quiring 

2012, Meyn and others 2007). Even fire-prone ecosystems in 

the middle range of the precipitation gradient are not constantly 

flammable, although the nature of the fire-climate relationship 

differs over the broad range of intermediate climates. Humid 

ecosystems, including many temperate forests, become most 

flammable under drought conditions (e.g., Lafon and others 

2005). On the other hand, moderately dry ecosystems, such 

as low- and mid-elevation forests and woodlands of the 

Southwestern United States, witness more burning after years 

with anomalous wetness; flammability is increased due to the 

production of fine fuels (during wet periods) that subsequently 

dry and become receptive to the ignition and spread of fire (e.g., 

Ireland and others 2012).

Third, burning occurs most frequently on landscapes with large 

fire compartments. A fire compartment is an area with continuous 

fuel through which a fire can spread unimpeded by streams, 

cliffs, or other firebreaks (Frost 1998). Large fire compartments 

often characterize flat terrain, where fires can sweep unimpeded 

across extensive uplands. Fire compartments are commonly 

smaller in hills and mountains because topographic complexities 

create fire breaks that limit the size of fires. All else equal, 

a landscape with smaller fires would burn less often than a 

landscape with larger fires. That is, small fires yield a long 

fire cycle.

Fire cycle is the number of years that would be required for fires 

to burn an area equivalent to the entire landscape (i.e., calculated 

as the reciprocal of the mean annual proportion of total land area 

burned) (Heinselman 1973). It is also known as fire rotation. If 

fires are small, they simply need a long time for their acreages to 

add up to an area the size of the landscape, unless the small fires 

are ignited at a very high density across the landscape.

Fire cycle is related to fire interval because it reflects the average 

fire interval for all points on the landscape (Kou and Baker 2006, 

Ward and others 2001). For example, a fire cycle of 10 years 

would indicate that each point on the landscape burns once every 

10 years, on average, although this cycle might actually result in 

some parts of the landscape burning once every 5 years and other 

parts at longer intervals. Fire cycle and fire interval are essential 

measures of a fire regime because they influence how much fuel 

accumulates between successive fires and which plant species can 

colonize between one fire and the next.

CURRENT APPALACHIAN FIRE CYCLE

Agency fire statistics can be used to estimate the current fire 

cycle by tallying the total acreage burned during the years for 

which the data were collected. Such calculations demonstrate 

that Appalachian fire cycles are long under fire exclusion. Fire 

statistics for the southern Blue Ridge Mountains of Tennessee 

and North Carolina (Barden and Woods 1974) show that humanignited wildfires burned 14,176 acres within Cherokee National 

Forest and Great Smoky Mountains National Park between 

1960 and 1969. The size of these two federally managed lands 

is 1,120,000 acres, or 79 times the acreage burned over the 

decade. To burn an area equivalent to the entire area, therefore, 

would require 79 decades, or 790 years. A 790-year fire cycle 

far exceeds the fire cycle/fire interval thought to have existed 

before fire exclusion (cf. Brose and others 2001). The fire cycle 

for lightning-ignited wildfires was even longer: 28,500 years for 

Great Smoky Mountains National Park, based on data for 1960–

1971, and 10,427 years for Cherokee National Forest, based on 

data for 1960–1969. A recent study (Flatley and others 2011) 

obtained comparable results using a longer (77-year) record of 

wildfires that burned Great Smoky Mountains National Park 

between 1930 and 2003: a cycle of 1,257 years for anthropogenic 

fires, 25,397 years for lightning-ignited fires, and 1,197 years for 

both ignition sources combined.

Further north in eastern West Virginia and western Virginia, 

a 34-year record of wildfires (Lafon and others 2005) yielded 

a similarly long fire cycle for an area spanning parts of the 

Appalachian Plateau, Ridge and Valley province, and Blue Ridge 

Mountains within Monongahela and George Washington National 

Forests, part of Jefferson National Forest, and Shenandoah 

National Park. The fire cycle was 1,001 years based on the 

combined record of human- and lightning-ignited wildfires 

between 1970 and 2003. Considering anthropogenic ignitions 

alone yielded a fire cycle of 1,196 years, and lightning ignitions 

gave a cycle of 6,138 years.

Shorter fire cycles have been calculated for some areas. A 70-

year record of fires that occurred across the entire State of West 

Virginia from 1939 to 2008 yielded a statewide fire cycle of 
Fire History of the Appalachian Region: A Review and Synthesis 9

192 years (Lynch and Hessl 2010). This record was compiled 

by the West Virginia Division of Forestry and includes fires 

that burned on private and State-owned lands, but not Federal 

lands. Therefore, it excludes the National Forest data analyzed 

by Lafon and others (2005). Similarly, a fire cycle of 204 years 

was obtained for Shenandoah National Park in the Blue Ridge 

Mountains of Virginia for the years 1930–2003 (Flatley and 

others 2011). But even these fire cycles are quite long compared 

to the shorter cycles of about a decade that are proposed for the 

pre-exclusion fire regime (e.g., Brose and others 2001).

If we ignore the precise fire cycle calculations and their variations 

between studies, the broad-brush picture that emerges is that the 

Appalachian region has witnessed little burning over the last 

few decades. Fire apparently is rare today because of the fire 

prevention and suppression campaigns waged since the early 20th 

century and because of the change in vegetation from flammable 

forests, woodlands, and grasslands to farm land and to less 

flammable forests containing mesophytic species (e.g., Harrod 

and others 2000, Nowacki and Abrams 2008). Fire prevention has 

undoubtedly reduced the density of ignitions, while suppression 

and landscape fragmentation (by farms, roads, etc.) have kept 

most fires small. If fires are kept small, most of the landscape will 

remain unburned for a long time (Ward and others 2001). The 

exclusion of large fires is the primary reason that fire cycles are 

so long today.

Examining the statistical distribution of fire size underscores 

the importance of large fires for the fire regime. In any fire 

regime, a handful of the largest fires are responsible for most 

of the area that is burned (Pyne 1982). The fire size distribution 

typically shows strong positive skew, where numerous small 

fires burn an acre or two apiece but contribute little to the overall 

fire regime while a handful of larger fires achieve most of the 

burning. For National Forest and National Park lands noted 

above in eastern West Virginia and western Virginia, a total 

of 1,557 anthropogenic wildfires occurred between 1970 and 

2003 (Lafon and others 2005). These fires burned 75,248 acres, 

giving a mean fire size of 48 acres. However, the median fire 

size was only 1 acre. Fires of 1 acre or less burned a total of only 

276 acres, or less than 1 percent of the entire acreage burned 

during the 34-year period. In contrast, the single largest fire of 

16,015 acres accounted for 21 percent of the total area burned 

during the period. Lightning ignitions showed a similar pattern, 

although fewer of them occurred (344 fires) and the maximum 

size was only 2,934 acres; the relatively limited extent of the 

fires explains why lightning-ignited fires had a longer cycle than 

anthropogenic fires.

GEOGRAPHIC VARIATIONS IN BURNING 

ACROSS THE APPALACHIAN REGION

The fire cycles documented here do not apply uniformly across 

the Appalachian region. Pronounced geographic differences 

are evident. These differences have been investigated for 

the previously mentioned area of eastern West Virginia and 

western Virginia by separating the fire statistics according to 

physiographic province (Lafon and Grissino-Mayer 2007). 

On the western side, Monongahela National Forest, which is 

located primarily on the high eastern edge of the Appalachian 

Plateau, witnessed exceptionally long fire cycles—10,845 years 

for all fires combined and 12,216 years and 96,637 years for 

anthropogenic and lightning-ignited fires, respectively. The 

fire cycles for the Ridge and Valley province to the east were 

shorter: 1,274 years for all fires combined, 1,472 years for 

anthropogenic fires, and 9,461 years for lightning-ignited fires. 

Fire cycles declined still farther to the east, where the Blue Ridge 

Mountains had fire cycles of 284 years for all fires, 347 years for 

anthropogenic fires, and 1,560 years for lightning-ignited fires.

This spatial gradient in fire cycle corresponded to a gradient 

in fire size (Lafon and Grissino-Mayer 2007). The fire sizeclass distribution became increasingly skewed from west to 

east for both ignition sources, with the Blue Ridge Mountains 

experiencing especially large fires. The maximum size of 

anthropogenic fires increased from 237 acres on the Appalachian 

Plateau to 4,357 acres in the Ridge and Valley province 

and 16,015 acres in the Blue Ridge Mountains, whereas the 

corresponding maximum sizes for lightning-ignited fires were 

141 acres, 551 acres, and 2,934 acres.

These spatial variations in fire cycle and fire size reflect 

differences of terrain, vegetation, climate, or human activities 

(Lafon and Grissino-Mayer 2007). The climate is cool and moist 

on the high eastern edge of the Appalachian Plateau, standing 

as it does in the path of eastward-moving storms. Orographic 

enhancement of the precipitation makes this one of the wettest 

and snowiest areas in the Eastern United States. The rain and 

late-lying snow probably keep the litter moist during much 

of the spring and thwart the ignition and spread of fire, and 

the mesophytic forests that cover most of the landscape yield 

relatively incombustible leaf litter.

The Ridge and Valley province is a drier environment. It stands 

in the rain shadow of the Appalachian Plateau, which intercepts 

moisture from the west, and of the Blue Ridge Mountains, which 

impede Atlantic moisture from the east (Lafon and GrissinoMayer 2007). Therefore, the Ridge and Valley province has 
10 Chapter 2. The Current Appalachian Fire Regime

the driest climate within the region, and its mountain slopes 

generally have well-drained, nutrient-poor soils derived from 

weathered sandstone and shale bedrock.1 These environmental 

conditions have favored the extensive cover of oak- and pinedominated forests that produce flammable litter. The broad, dry 

slopes, covered with xerophytic forest, would seem to present 

large fire compartments that make the Ridge and Valley province 

conducive to fire. 

The Blue Ridge province receives an amount of precipitation 

similar to the Appalachian Plateau (Lafon and Grissino-Mayer 

2007), and it has nutrient-rich soils with good water retention that 

are derived from weathered metamorphic rocks (see footnote 1). 

Therefore, its flammability must reflect factors other than the 

moisture conditions in this environment (Lafon and GrissinoMayer 2007). Fuel and terrain are probable contributors because 

the Blue Ridge Mountains also have broad slopes covered with 

oak- and pine-dominated vegetation. Precipitation variability 

is another potential factor. According to one hypothesis (Lafon 

and Grissino-Mayer 2007), differing regimes of precipitation 

delivery are more important than the mean annual precipitation 

in governing the geographic differences in fire across the 

Appalachian region. Subsequent work (Lafon and Quiring 

2012) supports this hypothesis. In particular, the Appalachian 

Plateau has relatively frequent, but light, precipitation events, 

which probably rewet the litter regularly enough that it is 

difficult for fires to ignite or spread. To the east, precipitation 

delivery becomes increasingly irregular so that in the Blue 

Ridge Mountains, and to some extent in the Ridge and Valley 

province, heavy precipitation events are separated by many 

consecutive rain-free days that permit fuels to dry and fires to 

ignite and spread. Thus, even though annual precipitation totals 

are similar between the Appalachian Plateau and the Blue Ridge 

Mountains, the differences in precipitation frequency seem to 

contribute to the vastly different fire regimes. In fact, the study 

of Lafon and Quiring (2012) shows that the link between burning 

and precipitation variability applies beyond the Appalachian 

Mountains to the entire temperate-forest region of the Eastern 

United States.

Climatic differences contribute to additional variations in fire 

activity across the Appalachian region. A comparison between 

Great Smoky Mountains and Shenandoah National Parks 

(Flatley and others 2011) shows that more burning occurs in the 

latter, with a fire cycle of 204 years, compared to 1,197 years 

in the former. These differences probably stem in part from the 

moister climate of the southern Blue Ridge Mountains. They 

could also reflect differences in human access. The narrow shape 

of Shenandoah National Park would seem to place more park 

perimeter near human activities and possibly expose the park 

to more human ignitions compared to Great Smoky Mountains 

1 Personal communication. April 21, 2016. Steven Q. Croy, Ecologist/Fire 

Planner, George Washington and Jefferson National Forests, U.S. Department of 

Agriculture Forest Service. 5162 Valleypointe Parkway, Roanoke, VA 24019.

National Park. However, the location of fires relative to the park 

boundaries suggests just the opposite—a greater percentage of 

fires was concentrated near the border of Great Smoky Mountains 

National Park compared to the percentage near Shenandoah 

National Park borders. Thus, human influences along the border 

are stronger for the Great Smoky Mountains. The differences in 

fire activity between the two parks appear, therefore, to reflect 

climatic differences.

A more probable influence of human ignitions on spatial patterns 

can be seen within the Appalachian Plateau. The analysis of West 

Virginia fires noted above (Lynch and Hessl 2010) depicted a 

gradient in which far more burning occurred in the southwestern 

part of the State than elsewhere between 1939 and 2008. Large 

fires (> 125 acres) were numerous in the southwest but virtually 

absent from the rest of the State. The southwest alone yielded 

a fire cycle of only 97 years, an unusually short fire cycle for a 

suppressed fire regime. Because the southwest is not the driest 

part of West Virginia, Lynch and Hessl (2010) proposed that 

non-climatic factors contributed to the widespread burning in that 

region: first, activities associated with widespread coal mining 

operations may have ignited many of the fires. Second, traditional 

cultural uses of fire may have persisted longer in southwestern 

West Virginia than elsewhere. Third, the rugged terrain may 

have hindered fire suppression. This last explanation seems to 

contradict the general understanding that fires grow larger on 

flat terrain than steep terrain, but that generalization probably 

applies best to unsuppressed fires. In the case of suppression, fires 

might spread farther on inaccessible terrain than on flatter, more 

accessible lands.

The cluster of large fires in southwestern West Virginia is part 

of a broader cluster extending southward along the Appalachian 

Plateau through Kentucky and Tennessee (fig. 2.02). This is 

one of the most extensive zones of burning in the entire Eastern 

United States, but whether it reflects the human influences and 

topographic constraints proposed by Lynch and Hessl (2010) is 

not known.

FIRE WEATHER AND CLIMATE

Implicit in considering wildfire in a humid region is that bouts of 

dry weather must occur periodically so that fuels can dry enough 

for fires to ignite and spread. Research conducted in temperate 

forests of the Northeastern United States (Pennsylvania, 

Wisconsin, and Michigan) (Haines and others 1983) demonstrates 

that the probability and number of fires can be predicted 

from basic weather variables (relative humidity or number of 

consecutive days since precipitation) or from fire-weather indices 

that incorporate multiple weather variables (precipitation, relative 

humidity, temperature, and wind speed).
Fire History of the Appalachian Region: A Review and Synthesis 11

We have performed a preliminary analysis of similar nature for 

the Ridge and Valley province of West Virginia and Virginia, near 

the center of the study region considered in this report, to explore 

how the probability of fire is related to dry spells. Specifically, 

we related the fire occurrence data of Lafon and Grissino-Mayer 

(2007) to the number of consecutive days without precipitation in 

at least one of four climate stations in the region. The number of 

consecutive dry days was calculated for the fire season (defined 

here as March through November) by using daily precipitation 

data obtained from the dynamic climate normal product of the 

National Climatic Data Center (NCDC) for the years 1970–2001. 

Fires occurred on 673 of the 8,800 days in the record, or about 

8 percent of all days, suggesting that for any given day there is 

a probability of 0.08 that fire will occur somewhere within the 

Figure 2.02—Locations (yellow dots) of large fires (> 500 acres in extent) in the Eastern United States for 

1984–2014 (from USDA USFS RSAC and USGS EROS 2016; see Eidenshink and others 2007).
0 2 4 6 8 10 12 14 16

0

5

10

15

20

25

30

Percent probability of ignition

Number of consecutive dry days

16 indicates ≥16 days

12 Chapter 2. The Current Appalachian Fire Regime

1,058,241 acres of National forest land. The fire probability 

for each day actually varies greatly, however, depending on 

the number of preceding rain-free days (see fig. 2.03) using 

equation (1):

P(F) = 0.0124D + 0.0231 (1)

where P(F) is the probability of fire and D is the number of 

consecutive dry days. As evident from the y-intercept, the 

predicted probability of fire on a day when precipitation occurs 

(i.e., zero consecutive dry days) is approximately 2.3 percent. 

In cases with one rain-free day (i.e., a single day that has no 

precipitation but when precipitation occurred the previous day), 

the predicted probability of fire on that single rain-free day is 

3.6 percent. Similarly, on a dry day preceded by 9 consecutive 

rain-free days (i.e., 10 consecutive rain-free days in total), the 

predicted probability of fire is 14.7 percent. This strong positive 

relationship underscores the importance of dry fuels to wildfire 

occurrence in the humid Appalachian Mountains and also 

suggests that it would be instructive to conduct a detailed study 

of Appalachian fire weather.

Of particular importance to fire weather are the broad, synopticscale atmospheric systems that contribute to rain-free days and 

strong winds. The classic synoptic work on fire weather in the 

United States is Schroeder and Buck’s (1970) handbook, Fire 

Weather: A Guide for Application of Meteorological Information 

to Forest Fire Control Operations. For regions east of the Rocky 

Mountains, Schroeder and Buck identified the periphery of 

surface high pressure systems as providing the most favorable 

fire weather because they combine dry weather and strong winds. 

Such weather is most commonly associated with Pacific Highs, 

which bring mild air masses that originate over the Pacific Ocean 

but lose much of their moisture by the time they have crossed 

the continent and arrived in the Appalachian region. The gusty 

weather at the leading edge of these air masses, along a dry 

cold front, is particularly favorable for fire. Fire weather can 

also accompany the cold, dry highs that originate in Canada. 

Additionally, the subtropical Azores High is especially important 

in the Southeastern United States, including the southern 

Appalachian Mountains, because of its tendency to stagnate 

over the region for a long period. When the Azores High extends 

westward to Texas, Gulf of Mexico moisture is cut off from the 

Eastern United States and prolonged drought can develop.

A more detailed synoptic study for the State of West Virginia 

(Takle and others 1994) identified eight surface patterns 

common in the Eastern United States and investigated the 

association of each pattern with fire. Again, periods associated 

with high pressure were shown to be important, particularly 

the windy “back-of-high” situation as the high drifts eastward. 

A terrain interaction occurs under the back of the high with 

orographic lifting of easterly winds over the eastern slopes of the 

Appalachian Mountains and drying/warming as air descends the 

western slopes into West Virginia. Consequently, this synoptic 

pattern accompanies the most extensive burning in the State. 

The pattern would not necessarily promote fire in eastern parts 

of the Appalachian region, however, because the orographic 

lifting sometimes generates rainfall along the eastern mountains. 

Additional studies of this sort are needed to understand the fire 

weather for other parts of the Appalachian region, particularly the 

Blue Ridge and the Ridge and Valley provinces where most of the 

federally managed lands are found.

Synoptic weather configurations are embedded in longer-term 

climatic patterns, and therefore the year-to-year variations in 

climate alter the occurrence of weather conditions that favor 

burning. Interannual climatic variations are often associated 

with global-scale circulation patterns, such as the El Niño–

Southern Oscillation (ENSO) phenomenon. Considerable 

research has been focused on the links between fire activity and 

ENSO or other circulation patterns in the Western United States 

Figure 2.03—Probability of ignition in the National forests in the Ridge 

and Valley province, West Virginia and Virginia, 1970–2001. Model 

R2 = 0.89, F = 115.0 (df = 1), P < 0.001. Probability of ignition increases 

with the number of consecutive dry days.
Fire History of the Appalachian Region: A Review and Synthesis 13

(e.g., Grissino- Mayer and Swetnam 2000) and parts of the 

Southeastern United States (e.g., Brenner 1991). In Florida, 

for example, burning often peaks during La Niña years, when 

dry-season rainfall is below normal (Beckage and others 2003, 

Brenner 1991, Goodrick and Hanley 2009, Harrison 2004). 

El Niño years, in contrast, are wetter and less conducive to fire. 

Analyses of such relationships have largely been lacking for 

the Appalachian region, but a preliminary investigation for the 

southern Blue Ridge Mountains (Baker 2009) suggested that 

anthropogenic fires burn more extensively during La Niña than 

El Niño years. This finding may reflect the abnormally wet 

weather that typically accompanies El Niño years in parts of 

the southern Blue Ridge Mountains (Climate Prediction Center 

2016). However, the finding may not apply to other parts of the 

Appalachian region, where the fall-winter-spring of El Niño years 

is usually drier and often warmer than normal (Climate Prediction 

Center 2016).

Correlating interannual variations in fire with annual variations 

in the Palmer Drought Severity Index (PDSI) (Palmer 1965) 

underscores the importance of dry conditions for fire in the humid 

Appalachian Mountains. PDSI, which is calculated by using 

a water-balance approach, assumes negative values under dry 

conditions and positive values under wet conditions. Measures 

of Appalachian fire activity—number of wildfires, area burned, 

and fire intensity—are negatively related to PDSI, meaning that 

fire activity increases as PDSI declines toward drier conditions 

(Baker 2009, Lafon and others 2005, Mitchener and Parker 

2005, Yaussy and Sutherland 1994). It is clear that temporal 

variations in climate and weather have an important influence on 

Appalachian burning, but more work is needed to gain a thorough 

understanding of the relationships among fire, drought, synoptic 

weather events, and global-scale atmospheric circulations.

IGNITION SOURCE AND SEASONALITY 

Whether fires are ignited by people or lightning is of interest 

because it pertains to the question of what is “natural” and how 

“natural vegetation” is maintained. Does lightning ignite enough 

fires to maintain fire-dependent vegetation such as pine and oak 

stands? Or are such communities merely artifacts of past human 

logging and burning?

These are difficult questions that cannot be fully answered with 

the data that are currently available. The questions connect to 

a larger debate about the role of aboriginal burning prior to 

European settlement (e.g., Denevan 1992, Vale 1998). Subsequent 

chapters on fire history offer partial glimpses, whereas this 

chapter provides context by reporting what is known about 

ignition sources today.

The foregoing discussion of present fire cycles indicates that 

anthropogenic fire cycles are shorter than those for lightningignited fires, primarily because a handful of the anthropogenic 

fires grow larger than any of the lightning-ignited fires. 

Anthropogenic ignitions also outnumber lightning ignitions 

and account for nearly all fires in some areas. Across the State 

of West Virginia, for example, 99.9 percent of all fires ignited 

between 2001 and 2008 were caused by people (Lynch and Hessl 

2010). Similarly, a study of all the National forests in the Ohio 

Valley (Illinois, Indiana, Kentucky, Missouri, Ohio, and West 

Virginia) found that 99 percent of the acreage burned was a result 

of anthropogenic fires (Yaussy and Sutherland 1994).

Lightning ignitions are a significant part of the fire regime in 

some parts of Appalachia, however. Lightning seems especially 

important on the eastern escarpment of the Blue Ridge and 

along some parts of the western escarpment and Ridge and 

Valley province (Baker 2009, Lafon and Grissino-Mayer 2007). 

An analysis of spatial patterns of fire (Lafon and GrissinoMayer 2007) in the Virginia–West Virginia study area noted 

above (Lafon and others 2005) revealed that lightning ignitions 

accounted for a greater proportion of wildfires along the 

eastern edge of the study area than in the west: 24 percent of 

fires in the Blue Ridge Mountains, compared with 18 percent 

in the Ridge and Valley province and only 8 percent on the 

Appalachian Plateau.

Most lightning-ignited fires and anthropogenic fires alike burn 

out before growing to a large size, but as discussed above, 

a few anthropogenic fires grow quite large, and therefore 

anthropogenic fires contribute more heavily to the fire cycle 

calculations. Fire seasonality helps explain why anthropogenic 

fires are responsible for most of the burning in Appalachia. Most 

anthropogenic fires burn during early to middle spring or in the 

fall, whereas lightning ignitions largely occur from mid-spring 

through summer (Baker 2009, Barden and Woods 1974, Lafon 

and others 2005, Yaussy and Sutherland 1994). The exact timing 

of the peaks in burning vary geographically over the region, but 

Appalachian fire regimes can be described generally as having 

a bimodal (spring/fall) anthropogenic pattern with a smaller 

unimodal distribution of lightning ignitions (fig. 2.04). The 

bimodal anthropogenic burning reflects the seasonal cycle of 

temperature, humidity, wind, precipitation, and plant phenology, 

which dictate the availability and flammability of fuels (Lafon 

and others 2005). The two peaks in fire activity coincide with the 

periods of the year when relative humidity is at its lowest and 

wind speeds are at their highest. Also, after the deciduous trees 

shed their leaves, sun and wind can penetrate to the forest floor 

and dry the dead litter, which is abundant and fluffy in fall and 
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

0

50

100

150

200

250

300

350

Anthropogenic 

fire

Natural 

fire

Area burned per month

(ac. /106ac.)

0.0

0.5

1.5

1.0

2.0

2.5

3.5

3.0

4.0

4.5

Mean fire density per month

(fires /106ac.)

Month

14 Chapter 2. The Current Appalachian Fire Regime

spring but less so in summer, when it has become more decayed 

and compacted. Some of the dead material is derived from 

herbaceous plants, and by summer much of this dead matter has 

also decayed and has been replaced by succulent green plants that 

do not readily burn.

Most lightning strikes occur during the summer when high 

humidity and closed forest canopy thwart drying of the litter on 

the surface and when vegetation is succulent and difficult to ignite 

(Lafon and others 2005). Lightning also usually accompanies 

rain, and therefore a lightning ignition would appear to require an 

unusually favorable combination of weather conditions (Lafon 

and Grissino-Mayer 2007), particularly if it is to spread and burn 

large acreages before it can be suppressed. Occasionally this 

happens, but not often. In contrast, people can light fires at any 

time of year, and therefore human ignitions dominate the spring 

and fall fire seasons when physical conditions most favor burning.

Lightning ignitions likely played a greater role in the past than at 

present because frequent burning would have maintained more 

flammable vegetation consisting of open woodlands with an 

understory of grasses and shrubs, such as blueberries (Vaccinium

spp.) (cf. Harrod and others 2000). The fine understory fuels 

would have dried rapidly after rain, enabling fire to spread from 

ignition points such as dry snags. Snags commonly serve as 

ignition points today (Lafon and others 2005). They can hold 

fire for up to several weeks until the moisture conditions of the 

surrounding fine fuel become conducive to the spread of fire 

(see footnote 1). Snags are common in old-growth forests today 

(Hart and others 2012), particularly on dry sites (McComb and 

Muller 1983), and they likely were abundant across Appalachian 

landscapes before the logging episode of the late 19th and 

early 20th centuries. Consequently, the vegetation that covered 

Appalachian mountain slopes in the past would appear to have 

been more favorable to lightning-ignited fires than the present 

vegetation cover.

The exact combinations of weather conditions that favor 

lightning ignitions are not known. This is a topic where additional 

research is needed, especially to understand the possibilities 

for implementing “wildland fire use” or “fires managed for 

resource benefit,” in which lightning-ignited (“natural”) 

wildfires are not suppressed but are allowed to burn to promote 

ecosystem restoration or other management goals. The relatively 

high incidence of lightning ignitions along the Blue Ridge 

Mountains suggests that terrain may contribute in some way to 

the development of lightning flashes during weather that is dry 

enough for burning. Solar heating of the Blue Ridge Mountain 

slopes may induce atmospheric convection in the absence of 

other convection-forcing mechanisms such as fronts or vertical 

wind shear, when high pressure persists over the region (Lafon 

and Grissino-Mayer 2007). These are precisely the conditions 

that would promote the drying of fuel because rainless and often 

sunny weather would prevail. During such weather, diurnal 

heating of the slopes generates convection (Bach and Price 2013), 

which can produce isolated thunderstorm cells. These scattered 

cells would not wet the fuels as continuously as an organized 

band of thunderstorms, and therefore the lightning that originates 

within these storms likely has a greater chance of striking 

dry fuel.

A recent study of single-cell thunderstorms over two summers in 

the Appalachian Mountains indicated that lightning activity was 

greatest over steep terrain, especially on the east- and southfacing aspects in the lee of major ridges (Miller and others 2015). 

These findings suggest the importance of morning and midday 

heating along the east- and south-facing slopes. As the warm air 

rises, it converges with the synoptic wind from the north or west, 

resulting in convection along the lee side. These results are not 

confined to the Blue Ridge province, and therefore they do not 

pinpoint why the Blue Ridge Mountains have more lightning 

ignitions than elsewhere. The Blue Ridge Mountains may be 

especially favorable because of their high relief or because 

Figure 2.04—Average number of fires (anthropogenic and natural) and area burned per month on federally managed 

lands of eastern West Virginia and western Virginia, 1970–2003. Based on data from Lafon and others (2005). The 

occurrence of anthropogenic fires is bimodally distributed, with peaks during spring and fall, whereas the incidence 

of natural, lightning-ignited fires is unimodally distributed with a peak in late spring-early summer.
Fire History of the Appalachian Region: A Review and Synthesis 15

they are exposed to incursions of humid, unstable air at low 

atmospheric levels from the Atlantic Ocean (Lafon and GrissinoMayer 2007). By impeding the westward flow of this air, the Blue 

Ridge Mountains may also inhibit convection over the Ridge and 

Valley province and the Appalachian Plateau. These mechanisms 

must remain speculative for now, however, because no research 

has been conducted to clarify how synoptic-scale weather 

interacts with Appalachian terrain to enable lightning ignitions.

TOPOGRAPHIC PATTERNS OF FIRE

Mountainous terrain can also lead to local-scale variations 

in disturbance frequency or severity because of topographic 

differences in runoff and exposure to precipitation, wind, and 

sunlight (Flatley and others 2011, Harmon and others 1983). In a 

humid region, where fuel production is not as limiting to fire as 

fuel moisture, fires might be expected to burn more frequently or 

severely on dry topographic positions (e.g., ridgetops or southfacing slopes) than in moist positions (e.g., valleys or northfacing slopes) (fig. 2.05).

Work in the Appalachian Mountains largely confirms that fires 

occur most frequently on dry sites, although it should be noted 

that topographic gradients of fire occurrence have been explored 

for only certain parts of the region—the National forests and 

National parks along the southern Blue Ridge Mountains of 

Tennessee and North Carolina (Barden and Woods 1974, Flatley 

and others 2011, Harmon and others 1983) and a section of the 

central Appalachians of Virginia and West Virginia spanning 

the eastern Appalachian Plateau, the Ridge and Valley province, 

and the Blue Ridge Mountains (Flatley and others 2011, Lafon 

and Grissino-Mayer 2007). Elevation is especially important, 

with fire most common at low elevations where the climate is 

relatively warm and dry and human access is easiest. In fact, 

lightning ignitions show a weaker relationship to elevation than 

anthropogenic ignitions.

Aspect and slope position also influence fire frequency; as 

expected, more fires occur on south- or west-facing slopes and 

on ridgetops than on other aspects (Flatley and others 2011, 

Harmon and others 1983, Lafon and Grissino-Mayer 2007). 

However, these patterns are not entirely consistent between study 

areas or are not statistically significant. Further, the strength 

of the topographic influence depends on the broad climatic 

setting. A spatial analysis of fire perimeter data for the two major 

Appalachian National parks revealed terrain influences under 

wet climatic conditions but not under dry conditions (Flatley and 

others 2011). This interaction was manifested in two ways. First, 

topographic patterns were stronger in the relatively wet Great 

Smoky Mountains National Park than in the drier Shenandoah 

National Park. Second, at each park, topographic patterns were 

relatively strong during abnormally wet years but not during 

dry years. Dry climatic conditions appear to render most of the 

landscape flammable and permit fires to spread readily across the 

landscape. Wet climatic conditions, on the other hand, confine 

burning more narrowly to the driest sites.

Figure 2.05—View toward the west slope of the Blue Ridge Mountains in Virginia, where a lightning-ignited wildfire killed large patches of forest during the 

dry summer of 2001. This fire was unusually severe because most Appalachian fires cause relatively little overstory mortality. In this photograph, taken toward 

the south-southeast in summer 2003, the remaining live trees are clearly visible in moist topographic positions. These moist sites include valley bottoms, 

ravines, and north-facing slopes, which face toward the viewer and slightly toward the left of the photograph. 
16 Chapter 2. The Current Appalachian Fire Regime

Local topographic influences on fire occurrence likely scale up 

to affect the overall fire regime of an entire landscape or region. 

A landscape with a drier climate should see larger fires because 

more of the terrain is flammable and therefore does not impede 

the spread of fires. Comparing Shenandoah and Great Smoky 

Mountains National Parks confirms such a pattern (Flatley and 

others 2011). The fire size distribution showed a stronger positive 

skew in Shenandoah, resulting in larger mean fire size (105 acres 

as compared to 63 acres) and shorter fire cycle (204 years as 

compared to 1,197 years).

Fire intensity and severity seem to follow similar topographic 

patterns as fire frequency, and they may be more ecologically 

important. Although fires often spread widely across terrain 

and encompass many topographic positions (e.g., Flatley and 

others 2011, Wimberly and Reilly 2007), they show topographic 

variations in both intensity (e.g., flame length, temperature) and 

severity (e.g., percent of plants killed, forest floor consumption). 

Studies of field data and remotely sensed images indicate that 

fires generally burn with greatest intensity and severity on dry 

ridges and upper slopes and on south- or west-facing aspects 

(Barden and Woods 1976, Hubbard and others 2004, Rush and 

others 2012, Vose and others 1999, Wimberly and Reilly 2007). 

These terrain patterns apparently reflect not only the topographic 

effect on fuel moisture but also the influence of the vegetation 

itself because stands dominated by flammable yellow pines cover 

the driest landforms. Even though yellow pines are more fire 

resistant than most other Appalachian tree species, they often 

sustain high mortality because of the intense burning in those 

stands. In turn, relatively severe burning usually benefits pine 

recruitment (Barden and Woods 1976, Harrod and others 2000, 

Jenkins and others 2011, Waldrop and Brose 1999, Welch and 

others 2000, Wimberly and Reilly 2007), thereby reinforcing 

topographic heterogeneity in vegetation and fire behavior.

Positive feedbacks of this nature probably operated in the past, 

when fire was a more important component of Appalachian 

landscapes. Although frequent burning would have limited 

the accumulation of woody fuels in the open pine stands, it 

would have fostered the thick growth of flammable grasses and 

shrubs in the understory (Harrod and others 2000). The regular 

burning of this combustible understory vegetation and pine litter 

would have thwarted the establishment of fire-sensitive tree 

species and perpetuated the existence of the open pine–grass 

structure, as seen in other ecosystems including the longleaf 

pine (Pinus palustris)–wiregrass (Aristida stricta) of the Coastal 

Plain (Christensen 2000), shortleaf pine (Pinus echinata)–little 

bluestem (Schizachyrium scoparium) of the Ouachita-Ozark 

Highlands (Hedrick and others 2007), and ponderosa pine (Pinus 

ponderosa)–bunchgrass of the Rocky Mountains (Peet 2000). If 

this interpretation is correct, the Appalachian yellow pine stands, 

which currently occupy upper slopes and south- and west-facing 

aspects, testify to a history of frequent burning in the past.

CONCLUSIONS AND IMPLICATIONS

The current fire regime appears inadequate to maintain pine 

stands, oak stands, and other fire-favored communities over the 

long term. Fire cycles are on the order of hundreds to thousands 

of years, even on landscapes dominated by flammable vegetation 

such as oak and pine forests. This means that fire return intervals 

for individual points and forest stands are also long. These long 

fire intervals differ greatly from those hypothesized for the past, 

when fires are thought to have occurred about once per decade in 

Appalachian oak forests (e.g., Brose and others 2001).

Analyses of the present fire regime contextualize and clarify 

the proxy records to be examined in subsequent chapters. The 

importance of fire size is particularly evident. Fire cycles—and 

fire intervals—are mostly determined by a handful of the largest 

fires, and because the fire size distribution is skewed more 

strongly in some parts of the Appalachian region than in others, 

certain landscapes witness much more burning than others. The 

Blue Ridge Mountains are especially favorable for large fires. 

This physiographic province has a variable precipitation regime 

with long dry spells that apparently enable fires to spread widely 

and burn large areas. The Blue Ridge province is also prone to 

lightning ignitions. These ignitions suggest that terrain-induced 

convection may initiate lightning strikes during relatively dry 

periods that permit fires to ignite and grow, although more 

study of this topic is needed before any firm conclusions can be 

reached. On the Appalachian Plateau, in contrast, the fire regime 

seems more strongly dominated by anthropogenic factors, such as 

cultural uses of fire in the coal fields.

Temporal patterns of burning largely reflect variations in weather 

and climate. Fire is associated with dry periods, whether at the 

time scale of days (e.g., synoptic weather configurations), seasons 

(spring and fall), or years (droughts, ENSO). These fire-climate 

associations suggest relationships to look for using proxy records 

of past fire regimes. As will be discussed in chapter 4, firescarred trees provide seasonally or annually resolved data that are 

informed by the relationships evidenced by current fire regimes.
Fire History of the Appalachian Region: A Review and Synthesis

17

Chapter 3. 

Forest Composition and Fire 

Before European Settlement as Inferred 

from Witness Tree Records

Beginning in 1785, Congress enacted a series of ordinances 

whereby surveying was executed along a rectangular system 

and its subdivisions known as the township and range system. 

This survey—the U.S. Public Land Survey System (PLSS)—

was completed in the early 1900s (Liu and others 2011). Each 

6-mile by 6-mile grid cell, or township, was further divided 

into 36 one-square-mile sections (Anderson and others 2006, 

Liu and others 2011). Each section consists of four corners and 

lines connecting each corner. Each line is also bisected by a 

quarter-corner (Anderson and others 2006, Manies and Mladenoff 

2000). At each of these intersections, surveyors placed posts or 

stones in the ground. In addition, they blazed two to four trees 

nearest each corner. These trees were known as bearing trees or 

witness trees. Surveyors identified these bearing trees to species, 

measured their diameter at breast height, and measured the 

distance between the trees and the corners. Surveyors were also 

instructed to make note of the general vegetation characteristics, 

such as abundance, transitions between vegetation types, burned 

areas, and suitability for cultivation (Batek and others 1999). This 

provided information about vegetation composition at intervals of 

one-half mile along any of the four cardinal directions (Anderson 

and others 2006) or about 24 trees per square mile (Black and 

others 2002). However, the rules for designating these trees 

changed through about 1850, likely leading to inconsistencies 

in the application of the rules and the development of possible 

biases (Bourdo 1956). These surveys were conducted over a 

short period of time, leading Oswald and Foster (2014) to refer to 

them as providing “snapshots,” in contrast to the “movie” that is 

available from metes and bounds.

Despite their utility, survey records regarding witness trees 

represent an unintentional, nonrandom, and non-impartial 

sampling effort. As a result, scientists have documented 

significant evidence for error, biases, and outright fraud in the 

survey records. Bourdo (1956) noted that field notes were often 

INTRODUCTION

European settlement activities significantly altered the 

disturbance regimes of forests across the Appalachian region 

(Dyer 2001, Foster and others 1998). During the 19th century, 

settlers cleared these forests at least once for timber and crop 

production or to make way for livestock grazing (Flatley and 

Copenheaver 2015). Many of the forests we observe today are 

actually second- or third-growth forests that developed after this 

initial clearing. A better understanding of forest composition 

before extensive clearing and settlement can help guide resource 

management and can also provide clues about the role of fire in 

shaping the vegetation. Some information about “presettlement” 

vegetation can be gained from surveyor records of “witness 

trees,” or “bearing trees” (Abrams and Ruffner 1995, Anderson 

and others 2006, Black and Abrams 2001, Black and others 2002, 

Bourdo 1956, Foster and others 2004).

Initial surveys of the Eastern United States during the colonial 

period (pre-1785) followed the metes-and-bounds system (Black 

and Abrams 2001). Survey routes and property boundaries often 

conformed to stream banks, trees, ridgelines, trails, and courses 

easily navigable across the landscape (Black and Abrams 2001, 

Thomas-Van Gundy and Strager 2012). This created a network of 

irregularly shaped property units across the original 13 colonies. 

The metes-and-bounds surveys were conducted gradually as 

settlers filled the lands that had been surveyed. As these lands 

became more densely settled over time, some existing parcels 

were split into smaller parcels to accommodate the growing 

population, and new parcels were carved from unsettled tracts 

of land. This gradual parceling of the land over time produced 

a record of continuous landscape change, which Flatley and 

Copenheaver (2015) compared to movies, i.e., “moving pictures 

as settlers moved west and divided up the land over time.” Most 

of the Appalachian region was surveyed by using the metes-andbounds system.
18 Chapter 3. Forest Composition and Fire Before European Settlement as Inferred from Witness Tree Records

fictitious or described township lines and corners that were 

never established. Notes also suggested that the time expended 

to establish the survey lines and mark the witness trees was too 

short to have been possible if the surveyors had actually followed 

the rules that were required. Survey lines may have deviated 

considerably from their intended route due to the use of improper 

or faulty equipment such as compasses. Black and Abrams 

(2001) suggested that surveyors often incorrectly identified tree 

species or interchangeably used common and uncommon names. 

Because surveyors were required to choose witness trees based 

upon their perceived economic value, size, age, abundance, and 

the ease with which they could be blazed, surveyors may have 

preferentially identified healthy or long-living trees rather than 

those actually near the survey lines or corners (Anderson and 

others 2006, Bourdo 1956). For example, Dyer (2001) suggested 

that in the northern portion of the Appalachian region, surveyors 

would have likely been biased to beech trees because their thin, 

smooth bark facilitated blazing. As a result, beech may have been 

interpreted as more abundant than it actually was.

Although witness tree records were not conducted to assess 

ecological communities, researchers have used these records to 

reconstruct characteristics of historic vegetation (e.g., Black and 

Abrams 2001, Liu and others 2011, Mladenoff and others 2002, 

Radeloff and others 1999, Schulte and Mladenoff 2005, Schulte 

and others 2002, Wang 2007). This has been accomplished at 

a variety of spatial scales, ranging from a local/county scale to 

a statewide scale (e.g., Friedman and Reich 2005). Based upon 

abundances of fire-dependent genera such as pine and oak, we 

can also use these records as an indirect means to assess the 

presence of fires. When complemented with direct evidence of 

fire from fire-scarred trees (chapter 4) and soil and sediment 

charcoal (chapter 6), the records allow us to paint a clearer 

picture of the role of fire.

Researchers have used witness trees for both “environmentally 

independent” and “environmentally dependent” analyses of past 

forest composition (Black and others 2002). Environmentally 

independent analysis relies solely on spatial patterns of witness 

tree records without direct regard for landscape features. Early 

studies using this approach were laborious because of the tedious 

efforts required for translating witness tree records onto maps. 

The laborious nature of the work limited the spatial extent of 

studies, but today the widespread availability of GIS (geographic 

information systems) software permits researchers to readily 

digitize records and to expand the spatial extent of the analyses 

using interpolation techniques (Black and others 2002, ThomasVan Gundy and Strager 2012). This has allowed for a more 

objective analysis of relationships between community data and 

underlying environmental variables (Batek and others 1999) as 

well as the development of spatially continuous representations 

of forest communities (Manies and Mladenoff 2000, Thomas-Van 

Gundy and Strager 2012). 

Environmentally dependent analysis may be used to establish 

species-site relationships using variables such as topography 

(e.g., slope, aspect, elevation, and landform type), soils, and 

hydrography. Through a statistical analysis associating species 

with these variables, researchers are able to assess potential 

controls on community composition. The drawback to this 

approach is that researchers must choose these variables 

a priori. As a result, these chosen variables may not be the most 

significant controls on community composition (Black and 

others 2002). 

OBJECTIVES AND METHODS

In the following sections, we briefly review studies that used 

witness tree records to reconstruct past forest composition in 

the Appalachian region (fig. 3.01, table 3.01). We compiled 

and reviewed peer-reviewed studies conducted over the past 

35 years. These studies used environmentally independent 

analysis, environmentally dependent analysis, or both. More 

studies were conducted for the Appalachian Plateau than for the 

other provinces. Some studies included multiple sites, which are 

treated separately in the graphs presented below. These studies 

encompass a range of areas, from local watersheds of 10 square 

miles to multiple counties exceeding 15,000 square miles. In 

addition, these studies examine historic forest composition across 

a wide range of elevations and actual witness trees transcribed 

(1,000–22,000).

This is perhaps the first quantitative synthesis of these studies, 

and our intent here is to offer a first-cut look at commonalities 

across them that will provide a resource for land managers. 

It is important to recognize that in our efforts to provide 

understandable generalizations, we have had to avoid extensive 

discussions regarding localized nuances as a consequence of 

micro-environmental and geological conditions.

We extracted data from these studies and grouped the study sites 

by physiographic province. Many of the studies report data on 

the total number of trees and on the percent of trees composed 

of each species. We used this information to calculate the total 

number of individuals of each species. We then aggregated 

the taxa into broad groups (pine, oak, other), because the firedependent pines and oaks are of particular interest for managers 

today. Several older studies only report percent composition, 

instead of both percent composition and abundance of each 

taxon, and consequently our aggregations for those datasets may 

be less accurate than for the other studies. Some studies also 

appear to include errors that prevented the species groupings 

from summing to 100 percent.

Several studies also use witness tree records in association with 

archaeological sites of Native American settlements to infer 

localized effects of anthropogenic activity on forest composition. 

We provide a brief review of the findings of these studies. 
Fire History of the Appalachian Region: A Review and Synthesis 19

Appalachian Plateau

Ridge and Valley

Blue Ridge

Piedmont

Physiographic province

Figure 3.01—Witness tree sites reviewed in this report. Purple polygons indicate areas across the Appalachian 

region in which corresponding witness tree records were analyzed; sources are listed beside the locations.
Table 3.01—Summary of information derived from studies reviewed in this chapter 

Source State

Physiographic 

province

Study 

area size Elevation

Number of 

witness trees

Warrant 

map dates

square miles feet

Abrams and Ruffner (1995) PA AP 15,158.70 750 - 2,570b 1,184 1765-1798

RV 737.2 530 - 1,930b

Abrams and McCay (1996),

Thomas-Van Gundy and Strager (2012),

Thomas-Van Gundy and Nowacki (2013)

WV AP, RV 2,662a 945 - 4,860b 1752-1899

Black and Abrams (2001) PA PD 968.5a 80 - 1,200b 9,880 1715-1725, 

1735-1765

Black and others (2002), 

Foster and others (2004)

AL RV, PD 13,000a 120 - 1,920b 43,610 1830-1850

Black and others (2006) PA AP 1,865 1,000 - 2,400b 166 1790-1820

Cowell (1995) GA PD 982.55 200 - 830b 11,511 1804, 1806

Dyer (2001) OH AP 4171a 500 - 1,100b 1788-1789, 

1796-1802

Flatley and Copenheaver (2015) VA RV 10.02 1,909 - 3,825 3,774 1786-2000

Shankman and Wills (1995) AL RV 144.74 1,634 - 4,902 1,057 1832

Wang (2007) NY AP 5,560 230 - 2,550 1797-1814

Whitney (1982) OH AP 1,405.65 800 - 1,400b 8,000+ 1810-1831

Whitney and DeCant (2003) PA AP 3,219.26 540 - 1,900b 6,000+ 1785-1840

Notes: Some studies (e.g., Abrams and Ruffner 1995) included multiple sites. In other cases, a single site was the subject of two studies (e.g., 

Black and others 2002, Foster and others 2004). 

AP = Appalachian Plateau, RV = Ridge and Valley, PD = Piedmont.

a Values reported in this table were obtained by using geographic information systems-based analysis and 30-m digital elevation data.

b Values either not reported explicitly by the study or only roughly estimated. 

20 Chapter 3. Forest Composition and Fire Before European Settlement as Inferred from Witness Tree Records

COARSE-SCALE INFERENCES REGARDING 

PRESETTLEMENT FOREST COMPOSITION

The percent composition of pine, oak, and other species are 

presented in fig. 3.02A–C. The sites are arranged on these graphs 

according to the physiographic provinces in which they were 

primarily located (some sites overlapped partially into a second 

province). Pine was relatively uncommon on the Appalachian 

Plateau (fig. 3.02A), but oak was relatively abundant (fig. 3.02B). 

White oak (Quercus alba) was especially common (Dyer 2001, 

Whitney 1982, Whitney and DeCant 2003). However, the 

“other” category represented the predominant tree group on 

the Appalachian Plateau (fig. 3.02C). Particularly important 

were sugar maple (Acer saccharum), American beech (Fagus 

grandifolia), yellow-poplar (Liriodendron tulipifera), and black 

cherry (Prunus serotina) (e.g., Abrams and Ruffner 1995, Dyer 

2001, Wang 2007). These results suggest that oak stands were 

intermixed with mesophytic forest, with oaks most common on 

the drier, less fertile soils and on fire-prone sites (e.g., Whitney 

and DeCant 2003). The high abundance of mesophytic species on 

the Appalachian Plateau probably reflects, in part, the relatively 

unfavorable fire environment (e.g., wetter climate) of the plateau 

compared to the other physiographic provinces (chapter 2). 

Geographic patterning of fire in the past will be considered 

further in chapter 4.

Fire-tolerant pines and oak were more prevalent in the Ridge 

and Valley and Piedmont physiographic provinces than on the 

Appalachian Plateau (fig. 3.02A and B); mesophytic species, 

in turn, were less common in the Ridge and Valley and the 

Piedmont than on the Appalachian Plateau (fig. 3.02C). The 

greater abundance of pine and oak and the limited number of 

mesophytic trees likely resulted from the relatively dry climate 

of the Ridge and Valley and the Piedmont provinces. A drier 

climate would have favored xerophytic species directly through 

the physiological adaptations of the species to low moisture and 

indirectly by promoting frequent and widespread burning. The 

terrain in these two provinces may also have created larger fire 

compartments than those on the plateau. In a study of the Georgia 

Piedmont, for example, Cowell (1995) found that pine and oak 

were common irrespective of topographic position, a finding that 

suggests fires burned widely across the landscape and enabled 

xerophytic species to occupy mesic sites from which they would 

have been competitively excluded in the absence of fire.
Percent composition

Study

Abrams & Ruffner

(1995)-AHP

Abrams & Ruffner

(1995)-AM

Abrams & Ruffner

(1995)-AF

Dyer

(2001)

Thomas-Van Gundy

& Strager (2012)

Wang

(2007)

Whitney

(1982)

Whitney &

Decant (2003)

Abrams & McCay

(1996)-AM

Abrams & McCay

(1996)-RV

Abrams & Ruffner

(1995)-RV

Flatley &

Copenheaver (2015)

Black &

Abrams (2001)

Black and

others (2002)

Cowell

(1995)

Shankman and

Wills (1995)

100

90

80

70

60

50

40

30

20

10

0

100

90

80

70

60

50

40

30

20

10

0

Presettlement pine composition

AP site RV site PD site

Percent composition

Study

Abrams & Ruffner

(1995)-AHP

Abrams & Ruffner

(1995)-AM

Abrams & Ruffner

(1995)-AF

Dyer

(2001)

Thomas-Van Gundy

& Strager (2012)

Wang

(2007)

Whitney

(1982)

Whitney &

Decant (2003)

Abrams & McCay

(1996)-AM

Abrams & McCay

(1996)-RV

Abrams & Ruffner

(1995)-RV

Flatley &

Copenheaver (2015)

Black &

Abrams (2001)

Black and

others (2002)

Cowell

(1995)

Shankman and

Wills (1995)

100

90

80

70

60

50

40

30

20

10

0

100

90

80

70

60

50

40

30

20

10

0

Presettlement oak composition

AP site RV site PD site

Percent composition

Study

Abrams & Ruffner

(1995)-AHP

Abrams & Ruffner

(1995)-AM

Abrams & Ruffner

(1995)-AF

Dyer

(2001)

Thomas-Van Gundy

& Strager (2012)

Wang

(2007)

Whitney

(1982)

Whitney &

Decant (2003)

Abrams & McCay

(1996)-AM

Abrams & McCay

(1996)-RV

Abrams & Ruffner

(1995)-RV

Flatley &

Copenheaver (2015)

Black &

Abrams (2001)

Black and

others (2002)

Cowell

(1995)

Shankman and

Wills (1995)

100

90

80

70

60

50

40

30

20

10

0

100

90

80

70

60

50

40

30

20

10

0

Presettlement composition of other taxa

AP site RV site PD site

(A)

(B)

(C)

Fire History of the Appalachian Region: A Review and Synthesis 21

Figure 3.02—Estimated 

presettlement forest composition 

across the physiographic provinces 

for (A) pine, (B) oak, and 

(C) other taxa. AP = Appalachian 

Plateau; RV = Ridge and Valley; 

PD = Piedmont. The x-axis 

indicates the data sources, 

where AF = Allegheny Front, 

AHP = Allegheny High Plateau, 

and AM = Allegheny Mountains. 
22 Chapter 3. Forest Composition and Fire Before European Settlement as Inferred from Witness Tree Records

LOCAL INFLUENCES OF ANTHROPOGENIC 

ACTIVITIES ON FOREST COMPOSITION 

AND FIRE ACTIVITY

Several of the studies we reviewed looked for relationships 

between anthropogenic activities and vegetation in areas around 

Native American settlements. The concern here is not with 

extensive burning that might have contributed to the widespread 

abundance of oaks, as considered above. Rather, the interest of 

some researchers has been in the more localized alterations in 

the abundance of fire-tolerant species in the vicinity of Native 

American settlements.

Black and others (2006) examined witness tree records in 

northwestern Pennsylvania in an effort to assess the impact 

of Native American influence on the presettlement landscape. 

Drawing on archaeological literature, they surmised that 

Native American influence was constrained to a radius of a 

few miles extending from a village. This suggestion reflects 

documented activities of clearing and burning for agricultural 

field development as well as for foraging and hunting. The 

human impact diminished as a function of distance, owing to the 

limitations of walking. These bits of information allowed Black 

and others (2006) to develop an index reflecting Native American 

influence that could then be statistically analyzed in association 

with forest composition. The authors found that high levels of 

human activity were associated with localized areas of high oak 

abundance. Clearing of the forest likely favored oaks due to their 

early successional traits, adaptions to fire, and ability to recruit 

rapidly. However, Black and others (2006) acknowledge that it is 

difficult to establish a causal relationship. Did Native Americans 

preferentially chose sites with fire-tolerant species as a source of 

wood, or did their activities promote the development of oak?

In Alabama, Foster and others (2004) found a relatively low 

abundance of pine around Native American settlements, and 

elevated levels of early-successional species such as elm and 

cedar. This evidence suggested that Native Americans favored 

pine wood for construction. The heavy use of pine apparently 

offset any benefits that pines would have gained from the 

elevated burning near settlements.

CONCLUSIONS AND IMPLICATIONS

Witness tree studies reveal vegetation patterns that are broadly 

consistent with the geographic patterns of forest composition 

and fire observed today (e.g., chapter 2). Xerophytic, firefavored taxa (oak and pine species) were common in the Ridge 

and Valley and the Piedmont physiographic provinces, whereas 

mesophytic species were abundant on the Appalachian Plateau. 

These spatial patterns show the direct influence of climate and 

terrain on moisture availability for plants. Additionally, variations 

in moisture across the region would have influenced flammability 

and thereby would have contributed to geographic patterns of fire 

and fire-adapted plants.

These interpretations of spatial patterning in vegetation across 

the physically diverse Appalachian region are bolstered by 

work conducted in neighboring regions surveyed under the 

PLSS. Witness tree analyses for those areas indicate that the 

distribution of fire-adapted tree species—such as longleaf pine 

on the Gulf Coastal Plain (Predmore and others 2007), shortleaf 

pine on the Ozark Plateau (Batek and others 1999), and jack pine 

(Pinus banksiana) in the Midwest (Radeloff and others 1999)—

corresponded with environmental gradients (e.g., moisture and 

topography) that would have influenced susceptibility to fire. 

Other, more fire-sensitive species showed opposing patterns 

along those same environmental gradients. Moreover, the PLSS 

records allow estimates of structural attributes such as tree 

density and diameter distributions. These estimates suggest that 

frequent burning maintained open woodlands or savannas with 

large, widely spaced trees (Batek and others 1999, Cox and Hart 

2015, Predmore and others 2007, Radeloff and others 1999).

A recent study using witness trees to identify spatial patterns 

of vegetation across an Appalachian landscape in eastern West 

Virginia (Thomas-Van Gundy and Nowacki 2013) classified tree 

species into two broad groups, “pyrophilic” and “pyrophobic.” 

Mapping the distributions of these groups by extrapolation from 

survey points indicated a shift from pyrophilic dominance in 

lower elevations and rain shadow environments to pyrophobic 

dominance in higher elevations and areas with orographically 

enhanced precipitation. Although this and other Appalachian 

studies rely on the metes-and-bounds survey system, and 

therefore cannot portray floristic and structural details, their 

results are broadly consistent with the work conducted in other 

regions; thus, these studies appear to offer reliable indications 

about the role of fire before widespread European settlement 

of the Appalachian region. Witness trees hold considerable 

promise for improving our understanding of Appalachian 

vegetation across the large sections of the region that remain to 

be investigated using these records.

At a local scale, presettlement species composition appears to 

have reflected the influence of Native American burning and 

land clearance near villages. Burning and cutting favored oaks in 

particular. However, it is not clear whether oaks were abundant 

during occupation of the villages or if instead they colonized after 

the villages were abandoned, when reduced fire frequency would 

have enabled oak sprouts to become established.
Fire History of the Appalachian Region: A Review and Synthesis

23

INTRODUCTION

Fire-scarred trees are one of the best sources of fire history 

information for understanding vegetation dynamics and guiding 

resource management (fig. 4.01). Scars offer direct evidence 

of past fires, including the year and often the season of burns 

and where the fires occurred. A fire-scar record compiled from 

multiple trees permits estimates of fire-free intervals (i.e., the 

elapsed time between successive fires), including how the 

intervals responded to land use change or climatic variations. Fire 

scars also provide information about fire extent and geographical 

variations in fire frequency. They offer a glimpse of fire regimes 

that existed decades or centuries before the industrial logging and 

fire exclusion eras.

A fire scar forms when a tree is injured by fire, but not killed 

(Craighead 1927, Dieterich and Swetnam 1984, Smith and 

Sutherland 1999, Weaver 1951). As new wood curls over 

the wound in subsequent growing seasons, the scar becomes 

embedded within the wood and the tree trunk. Multiple scars may 

accumulate within a tree over its lifetime if nonlethal surface 

fires are common. The scars form a distinctive, triangular-shaped 

feature termed a “catface” by foresters, extending from the tree 

base up the tree trunk (Arno and Sneck 1977) (fig. 4.02). By 

sawing through the catface of a living tree or snag to obtain 

a full or partial cross-section from the tree (fig. 4.03), the 

researcher captures the fire scars and can date them to their 

exact year of formation using the annual growth rings and 

dendrochronological techniques.

Vegetation scientists exploited this record of fire history as early 

as 1910, when Frederic Clements (1910) sawed cross-sections 

from fire-scarred lodgepole pines to reconstruct fire history 

back to 1707 in the Rocky Mountains of Colorado. Foresters 

and ecologists knew the importance of these fire-scar records 

early in the 20th century (Leopold 1924, Presnall 1933, Show 

and Kotok 1924), but it was not until the 1950s–1970s that 

researchers began applying tree-ring dating techniques to other 

coniferous forests of western North America (Houston 1973, 

McBride and Laven 1976, Wagener 1961, Weaver 1951) as the 

Figure 4.01—Fire-scarred pine, George Washington National Forest. Each 

vertical ridge on the uphill side of the tree was formed as wood curled over the 

portion of the tree wounded by a fire. Many fire-scarred trees, as this one, bear 

wounds received from multiple fires.

Chapter 4. 

Appalachian Fire History as 

Reconstructed from Fire-Scarred Trees
(A) (B)

24 Chapter 4. Appalachian Fire History as Reconstructed from Fire-Scarred Trees

Figure 4.02—Henri D. Grissino-Mayer sawing a fire-scarred pine snag, Jefferson 

National Forest. The distinctive triangular catface is visible at the base of the snag. 

Figure 4.03—Fire-scarred cross-sections. (A) Henri D. Grissino-Mayer sawing a 

cross-section from a fire-scarred snag, George Washington National Forest. (B) A 

sanded and dated cross-section cut from a living pitch pine tree on the George 

Washington National Forest. The scars on this cross-section record 13 different 

fires between 1845 and 1921. 

ecological importance of fire became evident to western forest 

managers. These researchers sought evidence from fire history 

studies to learn more about the role of fire and eventually inform 

management personnel to help guide the prescribed burning 

programs they were initiating. By the late 1970s, the utility 

of fire scars for reconstructing fire history had become widely 

recognized. Particularly important for this recognition was the 

detailed description of fire-scar sampling and analysis, published 

by the USDA Forest Service as General Technical Report INT-42, 

A Method for Determining Fire History in Coniferous Forests of 

the Mountain West (Arno and Sneck 1977).

Subsequent decades have seen an explosion of fire history 

research in the American West. Until about 15 years ago, 

however, little such work had been conducted in eastern North 

America. The paucity of studies on eastern fire history probably 

reflects several factors. First, little impetus existed to search for 

fire-scarred trees because fire was not widely considered to have 

played an important role in the temperate hardwood and mixed 

hardwood-conifer forests of eastern North America. Second, the 

dominance by hardwoods means that the fire history techniques 

developed in the West were not directly transferable to the East 

because hardwoods record scars less clearly and reliably than 

conifers. Several hardwood-based studies have been conducted 

(e.g., Hutchinson and others 2008, McEwan and others 2007), 

but conifers, especially pines, are superior recorders of fire 

history. Third, the humid climate found in the Eastern United 

States promotes rapid wood decay, which probably destroyed 

many dead trees that had contained fire scars. The decay problem 

is especially pronounced in hardwoods, many of which have 

catfaces that have rotted (fig. 4.04). In contrast, many pines 

saturate the wound with resin, which improves the resistance 

of the wood to future decay and extends the time for which 

the record of fire history is preserved. Well-preserved pine 

logs, especially the wounded portion saturated with resin, can 

remain on the forest floor for decades (fig. 4.05). Fourth, forest 
Fire History of the Appalachian Region: A Review and Synthesis 25

Figure 4.04—Decayed catface at the base of a beech tree, Jefferson National Forest.

Figure 4.05—Dead pine remnant (foreground) with fire scars, Great Smoky Mountains National Park. Many of these old, toppled 

pines still have dateable fire scars. The live pine in the background shows the wide base that may indicate a catface on the opposite 

side of the tree. (photo by Lisa B. LaForest)
26 Chapter 4. Appalachian Fire History as Reconstructed from Fire-Scarred Trees

clearance in the Eastern United States probably destroyed many 

fire-scarred trees such that researchers had to scour often rugged 

terrain to find stands with old trees that were not logged during 

the industrial logging episode. Finally, because many eastern tree 

species have shorter lifespans than their western counterparts, the 

lengths of the fire histories would be shorter and perhaps offer 

only limited information on the role of past fires.

Fortunately, however, field sampling conducted in eastern North 

America over the past 20 years has uncovered many sites across a 

broad geographic area of the Eastern United States that contained 

dead and living trees with considerable numbers of fire scars. The 

trees include pines in the Appalachian Mountains that preserve a 

record of fire history dating back to the 17th and 18th centuries. 

These pine-based fire chronologies are complemented by a few 

additional ones of similar length based on oaks. Together, the 

Appalachian fire chronologies form a fire-scar network (fig. 4.06) 

that portrays fire regimes across several physiographic provinces 

and over multiple land-use phases—beginning in several 

locations before European settlement and continuing through 

settlement, industrial logging and mining, and fire suppression.

Before synthesizing these results, however, we discuss the 

methods that are used to obtain them. It is critical to understand 

how the data are obtained and how reliably they can be used for 

estimating fire intervals or other fire regime parameters that are 

useful to resource managers.

FIELD SAMPLING FOR FIRE HISTORY

A fire-scarred tree preserves a record of at least some of the 

fires that burned at a specific point on the landscape. However, 

an individual tree may not record all the fires that occurred in 

its proximity. The reliability of individual trees for recording 

past fires is not well understood or quantified, but it is generally 

known that thin-barked trees are more sensitive to fire than 

trees with thick bark because their cambium is not as well 

insulated from heat (Brose and others 2014). A tree is therefore 

most susceptible to scarring when young. Once scarred, the 

tree remains susceptible to subsequent scarring because the 

bark sloughs off the scarred portion of the trunk and leaves it 

unprotected (Speer 2010), even as its diameter increases.

If a tree escapes scarring when small, it may become highly 

resistant to scarring as it grows larger and its bark thickens. A 

young tree could have escaped scarring for a number of reasons 

in the past, even if fires occurred at short intervals. For example, 

the tree might have been established in an unusually long firefree interval, during which it attained a large enough size to 

avoid scarring when frequent burning resumed. Moreover, fuel 

conditions might not have supported fires that would scar the tree, 

particularly if the tree were surrounded by sparse fine fuels or if 

the understory had a grass component that burned rapidly without 

attaining the prolonged high temperatures needed to scar the tree. 

The process of scar formation is too poorly understood to know 

whether trees grew into a “scar-proof” stage, but some evidence 

exists for it in the Appalachian region, where many old pine trees 

lack fire scars even in stands where neighboring trees have been 

scarred. Additionally, recent prescribed fires have created scars on 

scarred small-diameter pines while leaving larger ones unscathed.

Because of questions about the susceptibility of trees to scarring, 

researchers should sample in forest stands that contain numerous 

fire-scarred trees to improve the likelihood of capturing a 

thorough record of past fires. Increasing the number of firescarred samples increases the likelihood that a complete or nearcomplete census of fires is captured in the fire-scarred record. 

One study (Kou and Baker 2006) suggests that a sample size of 

at least 20 trees should be sought, but van Horne and Fulé (2006) 

found that a sample size approaching 50 randomly sampled 

fire-scarred trees would result in more accurate estimates of the 

census fire frequency. In the Appalachian region, dense clusters 

of fire-scarred trees are not available in many locations. However, 

our experience has shown that many Appalachian slopes have 

only one or a few fire-scarred trees. In some cases, one or two 

of these trees contain numerous scars, but such a small sample 

size for the stand is insufficient for thoroughly reconstructing 

fire history.

One strategy for enlarging the sample is to collect fire-scarred 

trees from a larger area. However, this strategy potentially 

introduces another bias because the larger area may capture 

additional fires that did not encompass the entire area, resulting 

in a decrease of the mean fire interval, the standard metric 

for quantifying fire frequency. It therefore may overstate the 
Fire History of the Appalachian Region: A Review and Synthesis 27

Figure 4.06—Locations of fire-scar network (shown as orange circles) across the Appalachian region 

reviewed in this report; sources are listed beside each location.
28 Chapter 4. Appalachian Fire History as Reconstructed from Fire-Scarred Trees

amount of burning within individual forest stands. In fact, if a 

large enough area were sampled—an entire national forest, for 

example—fires would probably be recorded every year, but it 

would be incorrect to conclude that all those fires affected an 

individual stand, which is often the initial spatial level of interest 

to land management agencies.

Consequently, to minimize both types of errors—missing 

fires that actually occurred or falsely attributing fires to points 

where they did not burn—Kou and Baker (2006) recommend 

collecting a large number of cross-sections (from approximately 

20 trees) within a small area (approximately 2.5 acres, or 1 ha), 

where the researcher could be reasonably confident that all the 

recorded fires actually occurred within that small area. However, 

van Horne and Fulé (2006) found that as few as 40 fire-scarred 

trees would capture the complete record of fires in a 247-acre 

(1-km2) area using a technique called targeted sampling, whereby 

the researcher samples only from the best fire-scarred trees 

instead of sampling them randomly. Probably more important 

than the absolute size of the sampled area is whether the area 

sampled represents a single fire compartment (sensu Frost 1998) 

that had continuous fuels through which fires could have spread, 

unimpeded by firebreaks, to all the sampled trees.

In practice, it can be impossible to find such concentrations 

of fire-scarred trees, and the studies synthesized below follow 

these recommendations to varying degrees. In some cases, the 

researchers were only permitted to sample opportunistically in a 

manner that precludes such a strategy. In an old-growth forest of 

eastern Kentucky, for example, McEwan and others (2014) were 

not allowed to cut any living trees, and therefore they based their 

fire history on 35 downed hardwood trees scattered over a 60-

acre area. Even though the study departed from the recommended 

minimum number of samples, it clearly made a valuable 

contribution, and in fact, the entire 60-acre site likely represents a 

single fire compartment. Restricted sampling opportunities should 

not discourage fire history studies in such locations, but we 

should recognize the potential limitations they impose, especially 

for comparing between studies that used different sampling 

strategies. In our synthesis below, we note the limitations to 

provide the reader with the best possible interpretations of the 

data that are available.

PROCESSING SAMPLES AND 

DATING FIRE SCARS

A primary means to reconstruct fire events is through 

dendrochronology, or tree-ring dating. To obtain accurate dates 

for each tree ring involves crossdating the rings by matching 

the tree-ring sequences of multiple trees in an area to ensure all 

rings are accounted for because individual trees may have locally 

absent rings or false rings caused by intra-annual ring density 

differences (Stokes and Smiley 1968). All trees in a region 

should display a similar pattern of ring-width variation over time 

because all are affected by the same regional climatic variations 

that operate year to year (Fritts 1976). A regional drought, for 

example, will induce slow tree growth, and hence a narrow 

annual ring will form in all trees. Over time, the trees establish 

a specific and recognizable sequence of wide and narrow rings 

that corresponds to changes in climatic favorability from year 

to year. By comparing the tree-ring series of multiple trees in a 

sample, the researcher can identify and correct any dating errors 

for an individual tree (Grissino-Mayer 2001a, Speer 2010). Even 

a dead tree (e.g., a log, standing snag, or smaller remnant sections 

of wood) can be dated by matching its outermost tree-ring series 

with the innermost ring patterns obtained from living trees 

(Stokes and Smiley 1968, Swetnam and others 1985). Dead trees 

found as standing snags or downed sections with catfaces are 

especially valuable for fire history because they usually contain 

the oldest fire scars at a site.

In the field, the researcher cuts cross-sections containing the 

fire scars from dead trees by using a chain saw and following 

established sampling techniques (Arno and Sneck 1977). 

Further, some smaller sections can be carefully cut from selected 

living trees to ensure that the record of most recent fire events 

is obtained (Heyerdahl and McKay 2001). In addition to these 

few fire-scarred living trees, researchers also core multiple trees 

from the same area (fig. 4.07) because these living trees ensure 

development of a chronology of tree-ring patterns that overlaps 

with the patterns obtained from the dead trees. Later, in the 

laboratory, the surface of each core and cross-section is smoothed 

by sanding with progressively finer-grit sandpaper to enhance 

the visibility of the tree-ring structure (Orvis and Grissino-Mayer 

2002). The tree rings for each specimen then are crossdated 

under a low-power boom-arm stereo-zoom microscope by using 

unusually narrow rings as markers by which to crossdate the 

specimen against the others. Graphical techniques of crossdating, 

such as skeleton plots (Swetnam and others 1985), are especially 

useful but many times the list method (Phipps 1985, Yamaguchi 

1991) can be used, especially in the Eastern United States. To 

verify and refine the crossdating, most dendrochronologists also 

measure the tree rings and statistically crossdate the ring-width 

series by using the program COFECHA (Grissino-Mayer 2001a, 

Holmes 1983). For dead trees, which have unknown dates, 

COFECHA matches the ring-width series against the living 

trees to assign the actual calendar year to each ring (GrissinoMayer 2001a).
Fire History of the Appalachian Region: A Review and Synthesis 29

Fire seasonality and potential ignition sources can be inferred 

from the location of the scar within an annual growth ring 

(Baisan and Swetnam 1990, Dieterich and Swetnam 1984, Lafon 

2010, Swetnam 1990, Swetnam and others 1999). Scars situated 

within the earlywood portion of the annual ring indicate fires 

that occurred during the early portion of the growing season, 

whereas middle-earlywood, late-latewood, and latewood scars 

may indicate summer burns, depending on the latitude and 

elevation of the study area. A scar situated between two annual 

rings is categorized as a dormant-season fire because the tree 

was not growing when the fire occurred. It is unclear, however, 

which year a dormant-season fire occurred. For example, a 

dormant-season scar between the rings for 1800 and 1801 could 

have formed in late 1800 or early 1801. Because these fires must 

be assigned to only one calendar year, researchers are informed 

by the current fire season and can assign one of the two years 

accordingly. For example, in the American Southwest, a dormant 

season fire is assigned the year after the fire scar because fires 

can occur in the dry months prior to onset of the North American 

Monsoon in early summer (Baisan and Swetnam 1990).

Figure 4.07—Students Steven Tarpley (left) and Will Flatley (right) removing increment cores from the base of a pine in Great Smoky Mountains 

National Park. (photo by Lisa B. LaForest)
30 Chapter 4. Appalachian Fire History as Reconstructed from Fire-Scarred Trees

Figure 4.08—Fire chart for Pine Mountain, Great Smoky Mountains National Park (LaForest 2012), created with the FHAES program. Each 

horizontal line represents the years covered by an individual tree. Dashed portions of the lines represent non-recording years, whereas solid 

portions represent recording years. Short vertical lines intersecting each horizontal line represent individual fire events. The vertical lines on the 

“Composite” axis at the bottom of the chart represent the record of all fires recorded by all trees at the study site.

Recorder year

Non-recorder year

Fire event

Injury event

Inner year with pith

Inner year without pith

Outer year with bark

Outer year without bark

Composite based on fire events and filtered by: 

- Number of trees recording fires ≥ 2

- Minimum number of samples ≥ 1

DEVELOPING A FIRE HISTORY

The creation of the FHX2 program between 1992 and 1995 

represented an important step in fire history research. FHX2 and 

its successor FHAES enable the researcher to enter and archive 

fire history data in the internationally accepted fire history 

exchange (FHX) format (Grissino-Mayer 2001b) and display 

the fire events in a composite fire chart (figs. 4.08 and 4.09). 

The main benefits of FHX2, however, are the many statistical 

analyses that can be performed on the fire history data once 

entered to gain more information on the overall fire regime. The 

program calculates several fire interval statistics, including the 

widely used mean fire interval (MFI), which is the average of all 

the fire intervals in the sample. Additionally, because fire interval 

data often are not normally distributed, FHX2 fits a Weibull 

distribution to the fire interval data and calculates the Weibull 

median interval (WMI, also called the Weibull median probability 

interval, or WMPI), which is considered a better estimate of the 

typical fire interval (Grissino-Mayer 1995, 1999, 2001b).

Measures of central tendency in fire interval data, such as 

the MFI and WMI, are not the only metric that matters when 

evaluating a fire regime. The variation in interval length can 

have important implications for understanding the role of fire 

events on tree establishment patterns. For example, an occasional 

long interval between successive fires may be needed for tree 

seedlings to grow tall enough to survive subsequent fires. 

FHX2 calculates several measures of variability, including 

standard deviation (SD), range of observed intervals, and the 

lower exceedance interval (LEI) and upper exceedance interval 

(UEI) (Grissino-Mayer 1999). LEI and UEI represent the 

bounds between which most intervals would be expected to fall, 
Fire History of the Appalachian Region: A Review and Synthesis 31

Figure 4.09—Portion of an idealized fire chart illustrating how to interpret the symbols. Each individual horizontal 

line (two of which are marked by blue brackets) represents the time spanned by an individual tree sample. Solid black 

portions of a line indicate recording years in which the tree is considered to have been susceptible to scarring. Dashed 

portions represent non-recording years. Short vertical lines indicate years with dated fire scars. The time elapsed between 

fires (marked by brown brackets) is the fire interval. The point mean fire interval (MFI) is calculated by averaging the 

fire intervals across all trees for recording years. The bottom line labeled “Composite” shows every year in which a fire 

was recorded by one or more sampled trees in the study site. The composite MFI is calculated by averaging the intervals 

between fires represented on the composite axis. The filtered composite MFI is calculated by averaging the intervals 

between “major” fires that are recorded on the composite axis. Major fires in this example are indicated by heavy 

vertical lines on the composite axis. These major fires include only those for which the following two criteria are met: at 

least two recording trees are scarred in a single year, and at least 25 percent of all recording trees are scarred that year.

according to the Weibull-modeled distribution of fire intervals. 

Most studies use the FHX2 default of 75 percent to define 

the LEI and UEI; i.e., 75 percent of all fire intervals would be 

expected to fall between the LEI and UEI. Of the remaining 

25 percent of intervals, the 12.5 percent below the LEI are the 

unusually short intervals, and the 12.5 percent above the UEI 

are unusually long for the site (see Brose and others 2013, 2015; 

Grissino-Mayer and others 2004). 

An important issue concerns the metrics used to evaluate 

the overall fire regime for an area because these metrics are 

influenced by the number of fire-scarred trees sampled and 

the overall area represented by the trees. For example, was 

the sample size too small, in which case the calculated fire 

intervals may be too long? Were the samples collected from a 

large geographic area, in which case the fire intervals would be 

atypically shorter? Basically, how can we compare metrics for 

fire interval data between sites with different sample sizes and 

different areal coverage?

Especially critical in fire history studies is accounting for the 

“imperfect recorder” problem when analyzing fire scars because 

otherwise the interval length could be grossly overestimated. For 

a given tree, only certain years are considered “recorder” years 

and should be designated as such when entered in FHX2/FHAES 

(Grissino-Mayer 2001b). Recorder years refer to those rings 

that developed in the years after an initial scar and are therefore 

capable of recording subsequent fires. This initial scar increases 

the susceptibility of that tree to subsequent scarring (see recorder 

intervals in fig. 4.09). Because many pines and oaks have thick, 

protective bark, they may have endured many fires before the 

first scar; therefore, no fire interval exists before the first scar. 

Similarly, if the tree heals over the wound, the years after the 

last fire scar formed prior to closure are no longer considered 

recorder years. Finally, tree rings of a fire-scarred cross-section 

that are obscured by burning or decay, whereby one cannot tell 

if a fire scar could have been present, are also not considered 

recorder years (figs. 4.09 and 4.10). By limiting the analyses to 

recording intervals, the researcher ensures that calculations are 

based only on periods that are covered by fire-scar data. Yet the 

imperfect recorder problem cannot be fully surmounted as even 

the designated recording intervals likely fail to record some fires.

Researchers have learned that important information on fire 

regimes can be gained by analyzing fire history at the individual 

tree point level. The “point fire interval” involves no compositing, 

i.e., consolidating all fire interval data from many trees into 

one time series. Fire intervals are calculated at the level of the 

individual tree, and the MFI, WMI, etc., for all these intervals are 

calculated (fig. 4.09). When considering a broader geographic 

area, however, fire-interval lengths will be overestimated, and 

the point fire interval will yield the most conservative estimate of 

fire frequency. It represents the longest possible fire interval for 

an area. 

More often, though, the fire history researcher will composite 

the fire events in multiple ways and report fire interval statistics 

(MFI, WMI, SD, range, LEI, and UEI) for each level of 

compositing. The “composite fire interval” provides a way to 

compensate for the imperfect recorder problem by combining the 

fire record for all the trees at a site into one composite time series 

(fig. 4.09). The more trees sampled, the lower the likelihood of 

missing a fire. As long as the trees were sampled within a small 

area, i.e., a single fire compartment, the composite fire record 
32 Chapter 4. Appalachian Fire History as Reconstructed from Fire-Scarred Trees

site in the Ridge and Valley section of eastern West Virginia 

(Schuler and McClain 2003), with an average of 6.8 years across 

all sites. However, the statistical distribution of these composite 

MFI estimates is positively skewed (fig. 4.11A), and therefore 

the median value (5.4 years) better represents the central 

tendency. These composite MFI estimates indicate that in the 

most frequently burned location, fires burned at least part of the 

study site about once every 2 years. Whether fires encompassed 

the entire study site that frequently cannot be determined from 

the composite fire-scar record because it combines all the scars 

from the entire study site into a single record, as described above 

(fig. 4.09). The composite WMI is similar to the MFI and ranges 

between 1.7 and 17.1 years across the various sites, with an 

average of 5.6 years.

Some of the reported differences in estimates of fire interval 

appear to result from differences in sample size. Shorter fire 

intervals are estimated for fire history sites with large sample 

sizes than for those with small sample sizes (fig. 4.12A). This 

relationship probably reflects the ability of larger samples to 

capture more fires, although the scatter among points indicates 

that differences in reconstructed fire intervals do not merely 

reflect sample size but also show the influence of actual controls, 

such as climate and terrain.

should yield the most reliable estimates of metrics that define the 

fire regime. Many researchers also calculate the composite fire 

interval by using any of several “filters” that will include only 

fire years in which a minimum number of recorder trees (usually 

two trees) and a minimum percentage (usually 10 percent or 

25 percent) were scarred (Grissino-Mayer 1995, 2001b; GrissinoMayer and others 1995; Swetnam 1990). The resultant “filtered 

composite fire interval” may characterize the typical interval 

for fire compartments on a landscape if fire scars were sampled 

from multiple fire compartments. For example, van Horne and 

Fulé (2006) performed an exhaustive census of fire-scarred trees 

from a 247-acre (1-km2) area of ponderosa pine forest in northern 

Arizona and found that the 25-percent filter offered the most 

reliable fire interval estimates. By reporting multiple fire interval 

calculations, including the point fire interval, the composite fire 

interval, and filtered composite fire intervals, a researcher can 

provide a range of estimates that cluster around the actual fire 

interval. Despite attempts to capture a complete inventory of 

fire events for an area, it is nonetheless impossible to know how 

many past fires were not recorded because they did not scar any 

trees in the sample. As such, fire interval metrics always provide 

a maximum length between successive fires for the study area. 

Should methods be found later that could reveal such “invisible” 

fire events (e.g., by using chemical changes of wood in the treering record), then these newly discovered fire events will actually 

serve to further reduce the average time between successive fires.

In considering the fire history results reported below, we note 

that many fire history studies conducted in the Eastern United 

States have not followed these standard sampling and reporting 

protocols. Many did not distinguish or tally recorder and nonrecorder years, for example, which would bias any estimates 

of fire interval metrics and affect the overall description of the 

local fire regime. Some used only one compositing method 

while others did not include a fire chart. The inconsistency 

and incompleteness have limited some of the analyses we 

attempted for this synthesis and therefore have constrained 

our interpretations.

FIRE INTERVALS RECONSTRUCTED 

FOR THE APPALACHIAN REGION

We identified 19 studies reporting analyses of pre-exclusion fire 

history in the Appalachian region (table 4.01). Of the 44 sites 

included in these studies, 21 had fire interval data extending 

back before 1850, but for the remaining sites fire intervals cover 

only the late 19th century through the 20th or early 21st century. 

The fire interval statistics reported in these studies—or that we 

calculated from them—indicate that fires burned frequently 

across the Appalachian region before pervasive anthropogenic 

fire exclusion practices disrupted these fire regimes (table 4.02).

Composite fire intervals were calculated and reported for nearly 

all the study sites (table 4.02). The composite MFI varies between 

1.9 years for a study site in the Great Smoky Mountains of 

Tennessee, which was dominated by pitch pine and chestnut oak 

(LaForest 2012), and 19.5 years for a northern red oak-dominated 

Figure 4.10—Pine cross-section with 

scars damaged by fire. A few dateable 

scars are present on this cross-section, 

but others may have been destroyed.
Table 4.01—Fire-scar studies and study sites synthesized in this report 

Source Site name

Phys. 

Prov. Elevation Topo. pos. Genus N

Record 

length

feet years

Aldrich and others (2010, 

2014)

Kelley Mtn. BR 3050-3310 W Pinus 92 1638-2005

Mill Mtn. RV 2260-2950 W 63 1704-2003

Reddish Knob RV 2070-2950 W 76 1671-2005

Armbrister (2002) GSMNP BR 2280-3800 SW Pinus 9 1860-2001

Brose and others (2013, 

2015)

Long Branch Hill AP 1700-1800 NW Pinus 35 1633-2010

Slate Run 1750-1900 NW 30 1623-2010

Upper Dry Run 1550-1830 NW 28 1635-2010

DeWeese (2007) Brush Mtn. RV 2790-2950 W & SW Pinus 36 1758-2002

Griffith Knob 3610-3770 W 36 1764-2004

Little Walker Mtn. 2620-3020 N 23 1778-2004

North Mtn. 2200-2490 NW 18 1742-2003

Feathers (2010) CRX BR 2000-2030 SE Pinus 15 1735-2008

CRT SE rdg. top 20 1720-2008

Flatley and others (2013) House Mtn. RV 1700-2000 Ridge top/

upper slopes

Pinus 82 1763-2009

Licklog Ridge BR 2300-2950 S & SE 116 1729-2009

Linville Mtn. 3180-3660 S & W 44 1725-2009

Harmon (1982) GSMNP BR 850-3090 — Pinus 43 1856-1979

Hessl and others (2011) Pike Knob RV 4100-4300 S & W Pinus 25 1868-2008

11 1887-2010

Quercus 16 1885-2001

Hoss and others (2008) Peters Mtn. RV 2000-2690 W Pinus 73 1794-2005

Hutchinson and others 

(2008)

REMA2 AP 820-1050 E, S Quercus 29 1877-2000

REMA3 22 1878-2000

Zaleski2 24 1870-2000

Zaleski3 25 1914-2000

Tar Hollow 2 22 1883-2000

Tar Hollow 3 17 1900-2000

LaForest (2012) Gold Mine BR 1510-1970 W Pinus 45 1728-2007

Rabbit Creek 1640-1970 NW 36 1763-2008

Pine Mtn. 1640-1970 W 36 1727-2007

Maxwell and Hicks (2010) Endless Wall AP 1900 S Pinus 21 1914-2005

McEwan and others (2007) Eagle Mill AP 660-1310 N, E, S, W Quercus 26 1917-2005

Watch Rock 33 1936-2005

Ball Diamond 22 1878-2002

Arch Rock 31 1900-2005

Raccoon Creek 25 1889-2005

Shawnee 20 1889-2005

Road Branch 20 1885-2002

Dickerson Hollow 20 1893-2002

Silver Creek 28 1879-2005

McEwan and others (2014) Big Everidge Hollow AP 1050-1970 E Quercus 21 1678-2009

Schuler and McClain (2003) Pike Knob RV 4270 E Quercus 20 1869-2002

Shumway and others (2001) Big Savage Mtn. AP 1970-2200 S & E Quercus 20 1616-1997

Sutherland (1997) REMA AP 790 N Quercus 14 1871-1995

Note: The Genus column indicates which genus of trees was sampled for fire scars. The N column indicates the number of scarred 

trees in the sample.

— = no data reported from study.

Phys. prov. = physiographic province; Topo. pos. = Topographic position; AP = Appalachian Plateau; BR = Blue Ridge; RV = Ridge 

and Valley; GSMNP = Great Smoky Mountains National Park; CRX = Cooper Ridge “Near” site; CRT = Cooper Ridge “Far” site; 

REMA = Raccoon Ecological Management Area.

Fire History of the Appalachian Region: A Review and Synthesis 33
Table 4.02—Calculations of fire interval for the study sites described in table 4.01 

Source Site name

Composite

10 percent 

filter

25 percent 

filter Point Decadal 

fire 

MFI WMI MFI WMI MFI WMI MFI WMI index

---------------------------------years---------------------------------

Aldrich and others (2010, 

2014)

Kelley Mtn. 3.9 3.7 — — 5.8 5.5 7.1 7 0.9

Mill Mtn. 5.4 5.1 — — 7.8 7.5 11.1 10.2 0.7

Reddish Knob 4.8 4.6 — — 8.2 7.4 12.5 11.3 0.7

Armbrister (2002) GSMNP 7.5 6.8 — — — — 5.6 — 0.7

Brose and others (2013, 

2015)

Long Branch Hill 19.4 11.2 — — — — 22.1a — 0.2

Slate Run 14 9.4 — — — — 25.4a — 0.2

Upper Dry Run 10.9 6.3 — — — — 13.3a — 0.3

DeWeese (2007) Brush Mtn. 4.1 3.3 9.8 8.1 — — 11.9 — 0.7

Griffith Knob 2.3 1.9 5.8 4.3 — — 13.4 — 0.6

Little Walker Mtn. 2.8 2.6 4.6 4.1 — — 8.9 — 0.7

North Mtn. 3.2 2.6 7.7 6.5 — — 11.5 — 0.8

Feathers (2010) CRX 6.2 5.6 — — — — 8.1 — 0.5

CRT 3.4 3 — — — — 10.7 — 0.4

Flatley and others (2013) House Mtn. 2.6 2.1 — — 7.9 6.5 9.8 8.1 0.8

Licklog Ridge 2.2 2 — — 4.6 4.4 9.1 8 0.7

Linville Mtn. 4 3.4 — — 6.5 5.8 13.1 11.1 0.6

Harmon (1982) GSMNP — — — — — — 12.7 — —

Hessl and others (2011) Pike Knob — — 7.1 6.3 — — 14.1 — 0.4

— — 9.4 7.9 — — 15.8 — 0.4

— — — — — — 49.8 — —

Hoss and others (2008) Peters Mtn. 2.5 2.2 — — 12.5 12.3 18.4 16.7 0.6

Hutchinson and others 

(2008)

REMA2 9.3 9.1 — — — — — — —

REMA3 9 9.2 — — — — 13a — 0.1

Zaleski2 14.5 11.3 — — — — — — —

Zaleski3 — — — — — — — — —

Tar Hollow 2 — — — — — — — — —

Tar Hollow 3 — — — — — — — — —

LaForest (2012) Gold Mine 2.1 1.8 2.6 2.2 5 4.2 10 — 0.6

Rabbit Creek 1.9 1.8 3.1 2.6 5.6 5.2 10.3 — 0.7

Pine Mtn. 2.4 2.1 3 2.6 7.3 6.7 9.7 — 0.4

Maxwell and Hicks (2010) Endless Wall 4.5 3.2 — — — — 13.7a 0.2

McEwan and others (2007) Eagle Mill 2.1 1.7 — — — — — — —

Watch Rock 8.4 8.2 — — — — — — —

Ball Diamond 6.6 6.3 — — — — 12.1a 11.6 0.5

Arch Rock 9 8.1 — — — — — — —

Raccoon Creek 6.4 5.7 — — — — — — —

Shawnee 5.3 4.7 — — — — 5.3a 5.3 0.5

Road Branch 8.6 6.7 — — — — 7a 7 0.4

Dickerson Hollow 12.2 11.1 — — — — 15.6a 14.6 0.4

Silver Creek — — — — — — — — —

McEwan and others (2014) Big Everidge Hollow 9.3 — — — — — 34.7 — 0.2

Schuler and McClain (2003) Pike Knob 19.5 17.1 — — — — 35a — 0.1

Shumway and others (2001) Big Savage Mtn. 8.2 7.6 — — — — 29.6a — 0.3

Sutherland (1997) REMA 5.4 3.6 — — — — 10.2a — 0.2

Note: The column labels at top indicate the scar data on which the fire intervals were calculated (e.g., composite intervals were based on the 

composite record of all scars at the study site). 

MFI = mean fire interval; WMI = Weibull median interval; GSMNP = Great Smoky Mountains National Park; CRX = Cooper Ridge “Near” site; 

CRT = Cooper Ridge “Far” site; REMA = Raccoon Ecological Management Area.

— = no data reported in the study.

a = Estimated by us from the fire chart but not reported in the study.

34 Chapter 4. Appalachian Fire History as Reconstructed from Fire-Scarred Trees
0 5 10 20 25 30 35 45 50

MFI (years)

15 40

20

16

12

8

4

0

20

16

12

8

4

0

20

16

12

8

4

0

20

16

12

8

4

0

20

16

12

8

4

0

20

16

12

8

4

0

Frequency

(A)

(B)

(C)

Fire History of the Appalachian Region: A Review and Synthesis 35

Figure 4.11—Distribution of fire intervals among the studies reported in table 4.02: 

(A) composite mean fire interval (MFI), (B) filtered composite MFI (25 percent), 

and (C) point MFI.

The influence of these controls can be minimized by comparing 

among neighboring stands within a study site (fig. 4.12B–D). 

Each study site included four separate pine stands on a mountain 

slope (Aldrich and others 2010, 2014), and each stand contained 

a different number of fire-scarred trees. Because fire frequency 

probably was similar among the stands on a single mountainside, 

the observed differences in MFI likely reflect differences in 

the completeness of fire history records, with larger samples 

generally having a fuller record than smaller samples. Sample 

size appears to influence the estimates of fire interval. The trends 

suggest, in fact, that the site-level composite MFI (i.e., the MFI 

for all four stands combined) may offer the best portrayal of fire 

interval because it is the most thorough. Whether compositing 

across an entire site is appropriate, however, depends on 

how widely fires spread over the landscape. If fires routinely 

encompassed multiple pine stands, it would mean that the entire 

study site was part of a single fire compartment and should be 

analyzed as such. 

We will consider fire size and spread in more detail in a later 

section, but because the actual sizes of the fire compartments 

are not certain, it is important to analyze fire intervals through 

multiple measures to bracket a potential range. Unfortunately, 

few Appalachian fire history publications report filtered 

composite fire intervals (Aldrich and others 2010, 2014; Flatley 

and others 2013; DeWeese 2007; LaForest 2012). Of those 

applying the 25-percent filter (table 4.02; fig. 4.11B), MFI ranges 

between 4.6 and 12.5 years, with an average of 7.1 years and 

median of 6.9 years across the 10 sites for which it is reported. 

The corresponding WMI values are 4.2–12.3 years, with an 

average of 6.6 years. These results indicate that major fires 

burned a substantial portion of each study site at intervals of 

roughly 4–13 years with an average of about 7.0 years (GrissinoMayer 2016).

The estimates for the point fire interval are longer (table 4.02; 

fig. 4.11C), with MFI of 5.3–49.8 years (average 15.0 years) and 

WMI of 5.3–16.7 years (mean 10.1 years). For studies that do not 

report point MFI, we calculated it from the published fire charts 

and included it in table 4.02. These estimates are probably biased 

toward long fire intervals because some studies do not distinguish 

between recording and non-recording intervals. Nonetheless, 

even these conservative estimates indicate a quite high fire 

frequency for most study sites. At the most frequently burned 

Shawnee site in Ohio (McEwan and others 2007), fires can be 

interpreted to have occurred at every point on the landscape at 

about a 5-year interval, at least during the four decades (1889–

1931) represented at the study site. These decades encompass 

the period of frequent, severe burning associated with industrial 

land use, and unfortunately the Shawnee record does not extend 

further back in time. However, even some of the older fire 

chronologies have short intervals, as seen at Kelley Mountain in 

Virginia (Aldrich and others 2014), with a point MFI of 7.1 years 

for the period 1725–1921.
(A) All Sites (B) Kelley Mountain

(C) Mill Mountain (D) Reddish Knob

0 20 40 60 80 100 120 0 20 40 60 80 100 120

Sample size

20

16

12

8

4

0

20

16

12

8

4

0

Composite MFI

Comp. MFI = 11.167*exp(-0.005*Sample size)

R2

 = 0.012, p=0.859

Comp. MFI = 11.951*exp(-0.021*Sample size)

R2

 = 0.921, p=0.010

Comp. MFI = 8.451*exp(-0.012*Sample size)

R2

 = 0.186, p<0.01

Comp. MFI = 6.777*exp(-0.005*Sample size)

R2 = 0.360, p=0.285

36 Chapter 4. Appalachian Fire History as Reconstructed from Fire-Scarred Trees

Figure 4.12—Relationship between composite fire interval and sample size for (A) all studies 

reviewed in this report and (B–D) pine stands at three fire history study sites on the George 

Washington National Forest (Aldrich and others 2010, 2014). For B–D, the trend lines were fitted to 

the blue points, which indicate the composite mean fire interval (MFI) for the four individual stands 

at each study site. One of the blue points also indicates the point fire interval, which represents the 

sampling level of a single tree (i.e., fire scars were not composited and therefore the sample size is 

entered as one tree). Red points indicate site-level composite MFI, for reference; these points were 

excluded from the trend lines to avoid the assumption that an entire study site functioned as a single 

fire compartment.

VARIABILITY IN FIRE INTERVALS

Care should be taken, while focusing on MFI and WMI, 

not to overlook variations in fire interval, given that (1) the 

occasional long interval can have important consequences for 

plant regeneration, and (2) very short intervals between two or 

more successive fires can reduce the density of tree seedlings 

and saplings and thereby shape the forest/woodland structure 

that develops. For the studies reporting filtered composite fire 

intervals, the LEI and UEI indicate that intervals exceeding about 

10–15 years could be expected occasionally (table 4.03). At the 

Reddish Knob site, for example, 12.5 percent of the fire intervals 

are predicted to exceed 14.4 years (and 12.5 percent should be 

less than 2.7 years; also see fig. 4.13A–C).

From the modeled Weibull distribution, we can also estimate the 

probability of any specific interval. For example, oak seedling 

establishment may require an interval of at least 10–40 years to 

enable the seedlings to grow large enough to survive subsequent 

fires (Brose and others 2014). The broad range of 10–40 years 

suggests that the precise requirements for seedling establishment 

are uncertain. The requirements undoubtedly vary among oak 

species and depend on such factors as fuel load, fire behavior, and 

site productivity. For argument’s sake, we will assume a critical 

interval of 10 years. Using the Reddish Knob fire interval data, 

we find that 31.9 percent of the filtered composite fire intervals, 

or roughly one-third of them, would exceed this critical length 

(fig. 4.13D).
Table 4.03—Variability in fire interval based on the filtered composite firescar record

Source Site name

Lower 

exceedance 

interval

Upper 

exceedance 

interval Range

----------------- years-----------------

Aldrich and others (2010, 

2014)

Kelley Mountain 2.5 9.5 2-15

Mill Mountain 3.6 12.4 2-17

Reddish Knob 2.7 14.4 2-26

DeWeese (2007) Brush Mountain 2.3 18.6 1-29

Griffith Knob 1 11.7 1-19

Little Walker Mountain 1.5 7.9 1-12

North Mountain 2 14.5 1-21

Flatley and others (2013) House Mountain 1.9 14.9 1-26

Licklog Ridge 1.9 7.6 2-12

Linville Mountain 2.1 11.7 2-24

Hoss and others (2008) Peters Mountain 6.9 18.2 4-20

LaForest (2012) Gold Mine 1.3 9.2 1-13

Rabbit Creek 2.1 9.4 2-10

Pine Mountain 2.7 12.4 2-15

Fire History of the Appalachian Region: A Review and Synthesis 37

Would this fire regime, where one in three intervals exceeded the 

critical length, have been suitable for oak establishment? To find 

out, we would need to know how many years are required for 

three fire intervals to pass because one of those three intervals 

should exceed the 10-year threshold (on average). Reddish Knob 

had a filtered composite MFI of 8.2 years, so it burned three 

times every 25 years, on average (i.e., 8.2 years × 3 intervals ≈ 25 

years). This means that during every 25-year period, one interval 

was long enough to enable oak seedlings or sprouts to become 

established and attain a fire-resistant size: the fire regime appears 

to have provided ample opportunities for oak establishment. 

Because oak trees live more than 25 years, an oak population 

could have been maintained indefinitely under such a fire regime, 

with younger oaks regularly replacing old ones that died.

In contrast, if oaks actually require a 40-year interval without fire, 

the past fire regime was unsuitable—only about 0.001 percent 

(or 1 in 100,000) of the fire intervals would have been that long 

(fig. 4.13D). That is, only one interval in 820,000 years would 

have permitted oak establishment (i.e., 8.2 years × 100,000 

intervals = 820,000 years). An oak population could not persist 

on a site without one or more seedling establishment episodes 

during the typical lifespan of the trees, or about 50–100 years for 

the shortest-lived Appalachian oak species [scarlet oak (Quercus 

coccinea) and black oak (Q. velutina)] and 300 years for the 

longest-lived species [white oak (Q. alba) and chestnut oak 

(Q. montana)] (Loehle 1988). 

In truth, it would be impossible to identify a critical fire interval 

that applies to all oak species on all sites. Whether an interval 

provides enough time for oak establishment would depend in 

part on the fire resistance of each oak species and how rapidly a 

seedling or sprout could grow. On a site with favorable growing 

conditions (e.g., good soil), 10 years might be long enough for a 

particular species, but it could be insufficient on a droughty site 

where the seedlings grow slowly.

Interrelationships between plant growth and fire likely account 

for many of the vegetation patterns on Appalachian landscapes. 

For example, oak-hickory forests occupy moderately moist northor east-facing mountain slopes, while the more fire-resistant pines 

cover drier south- or west-facing slopes and ridges (fig. 4.14). 

On these dry slopes, only a few old oaks can be found scattered 

among the pines, suggesting that oak seedlings and sprouts 

generally did not establish and grow to a fire-resistant size during 

even the longest fire intervals. Moreover, fires may have burned 

hotter on the dry sites (see chapter 2), so a longer fire interval 
0 5 10 20 25 30 35

 Interval (years)

15 40

20

16

12

8

4

0

20

16

12

8

4

0

20

16

12

8

4

0

20

16

12

8

4

0

28

24

20

16

12

8

4

0

Probability (percent)

Frequency

min = 2.7

prg = 87.5%

min = 2

prg = 92.3%

max = 14.4

prg = 12.5%

min = 10

prg = 31.9%

max = 40

prg = 0.001%

max = 26

prg = 0.4%

(A)

(B)

(C)

(D)

38 Chapter 4. Appalachian Fire History as Reconstructed from Fire-Scarred Trees

Figure 4.13—Weibull distribution of filtered composite fire interval data from Reddish Knob, VA (Aldrich and others 2014), demonstrating 

(A) the actual frequency distribution of fire intervals (gray bars) with the modeled probability distribution superimposed (blue line), (B) the 

modeled probabilities of the minimum (2 years) and maximum (26 years) fire return intervals recorded at the site, (C) the modeled probabilities 

of the lower (LEI) and upper (UEI) exceedance intervals, and (D) the modeled probabilities of a 10-year and 40-year fire return interval.

would have been necessary for oaks to have attained a large 

enough size to enable them to withstand the high temperatures by 

developing thicker bark or more expansive roots around the base 

where little fuel could accumulate.

The persistence of pines on dry slopes apparently reflects the fire 

resistance of even fairly small seedlings. Some pines survived 

burning at ages as young as 4–7 years, according to fire-scar 

data, and at stem diameters as small as 0.6–4.5 cm. These are 

the minimum ages and diameters at which trees recorded their 

first scar at three sites in western Virginia (Aldrich and others 

2010, 2014), and they correspond with the ages (5–10 years) at 

which Table Mountain pine trees can bear cones (Gray and others 

2002). To be sure, it is unusual to find fire scars on such small 

trees, but even the average age at first scarring was quite young, 

between 12.6 and 19.7 years among the three sites, and average 

stem diameter was only 5.1–7.4 cm. Clearly, the Table Mountain 

and pitch pines are adapted to a rigorous environment (fig. 4.15) 

where poor, droughty soils constrain growth and fires recur at 

short intervals.
83°50'0"W 83°49'30"W

83°50'0"W 83°49'30"W

35°33'30"N

35°33'30"N

Stand type

Yellow pine

Oak–hickory

White pine–oak

Cove hardwood–

hemlock

mi

0.25

(B)

Fire History of the Appalachian Region: A Review and Synthesis 39

(A)

Figure 4.14—Vegetation distribution on Appalachian slopes. (A) View of the north slope of Brush Mountain, Jefferson National Forest. The view is toward 

the south, and pine stands are visible as the dark patches covering the west-facing slopes of spurs and surrounded by hardwood forest matrix. (B) Topographic 

distribution of forest types in a portion of Licklog drainage basin, Great Smoky Mountains National Park (Flatley and others 2013, 2015).
40 Chapter 4. Appalachian Fire History as Reconstructed from Fire-Scarred Trees

TEMPORAL CHANGES IN FIRE FREQUENCY

An important question arising from the fire interval analyses 

is how well they represent the preindustrial fire regime. It is 

the earlier fire regime(s) that are of most interest, especially 

to guide prescribed burning when attempting to restore and 

maintain fire-dependent vegetation. Therefore, if the industrial 

logging period had an anomalous fire regime, as suggested by 

the conceptual model presented in fig. 1.02 and repeated here in 

fig. 4.16, it would be useful to calculate fire intervals separately 

for the earlier periods to characterize the fire regime before 

the industrial impact was manifest. In this section, we look for 

temporal variations in the fire-scar records to ascertain how fire 

frequency varied under changing land uses.

To make such comparisons, we use a fire frequency index 

first calculated by Hoss and others (2008), referred to in this 

report as the decadal fire index (DFI). The DFI is calculated 

by first summing the number of fire scars recorded during each 

decade. This sum is then divided by the number of trees that 

are represented during that decade by at least one recorder year; 

dividing by the number of recording trees standardizes the firescar sum to permit comparison between decades with different 

sample sizes. When the DFI is graphed, it displays decade-toFigure 4.15—Dry oak-pine stand in the Blue Ridge Mountains, Jefferson National Forest.

1500

1540

1580

1620

1660

1700

1740

17801820

1860

1900

1940

1980

2020

Fire frequency

Year

Figure 4.16—Conceptual model of Appalachian fire history, after Brose 

and others (2001). According to this model, fires occurred regularly 

during aboriginal habitation and European settlement before spiking in 

frequency during the industrial logging episode of the late 1800s. The 

spike was followed by a rapid decline in fire frequency during the fire 

exclusion era that began in the early to mid 1900s.

decade variations in fire frequency and reveals long-term trends 

in fire occurrence (fig. 4.17). This index offers a conservative 

estimate of fire frequency because it does not composite the 

fire scars.
1600

1640

1680

1720

1760

180018401880

1920

1960

2000

Decade

2.4

2.0

1.6

1.2

0.8

0.4

0.0

2.4

2.0

1.6

1.2

0.8

0.4

0.0

2.4

2.0

1.6

1.2

0.8

0.4

0.0

2.4

2.0

1.6

1.2

0.8

0.4

0.0

2.4

2.0

1.6

1.2

0.8

0.4

0.0

2.4

2.0

1.6

1.2

0.8

0.4

0.0

Decadal fire index

Aldrich and others (2010, 2014)

Kelley Mountain, VA

Mill Mountain, VA

Reddish Knob, VA

1600

1640

1680

1720

1760

1800

1840

1880

1920

1960

2000

Decade

2.4

2.0

1.6

1.2

0.8

0.4

0.0

2.4

2.0

1.6

1.2

0.8

0.4

0.0

2.4

2.0

1.6

1.2

0.8

0.4

0.0

2.4

2.0

1.6

1.2

0.8

0.4

0.0

2.4

2.0

1.6

1.2

0.8

0.4

0.0

2.4

2.0

1.6

1.2

0.8

0.4

0.0

Decadal fire index

Brose and others (2013, 2015)

Long Branch, PA

Slate Run, PA

Upper Dry Run, PA

(A)

(B)

Fire History of the Appalachian Region: A Review and Synthesis 41

Figure 4.17—Temporal variations in the decadal fire index (DFI, thick colored lines) for 

(A) three study sites on the George Washington National Forest, Virginia, (Aldrich and 

others 2010, 2014) and (B) three study sites on the Tioga and Tiadaghton State Forests, 

Pennsylvania (Brose and others 2013, 2015). The thin black lines are regression lines fitted 

to the pre-exclusion decades.
Table 4.04—Summary of regression models analyzing trends in decadal fire 

index (DFI) over time

Source Site name

Decades 

covered

Number of 

decades R2 Trend

Aldrich and others (2010, 

2014)

Kelley Mtn. 1630–1929 27 0.006 0

Mill Mtn. 1700–1939 24 0.004 0

Reddish Knob 1670–1919 25 0.003 0

Brose and others (2013, 

2015)

Long Branch Hill 1600–1909 31 0.349 +

Slate Run 1600–1919 32 0.321 +

Upper Dry Run 1600–1919 32 0.425 +

DeWeese (2007) Brush Mtn. 1730–1939 21 0.142 0

Griffith Knob 1750–1939 17 0.151 0

Little Walker Mtn. 1770–1939 17 0.038 0

North Mtn. 1750–1939 19 0.197 0

Feathers (2010) CRX 1730–1939 21 0.031 0

CRT 1720–1939 22 0.284 +

Flatley and others (2013) House Mtn. 1760–1959 20 0.07 0

Licklog Ridge 1720–1919 20 0.056 0

Linville Mtn. 1720–1939 20 0.001 0

Hoss and others (2008) Peters Mtn. 1790–1949 16 0.1 0

LaForest (2012) Gold Mine 1740–1939 15 0.001 0

Pine Mtn. 1720–1939 18 0.304 –

Rabbit Creek 1760–1939 18 0.053 0

McEwan and others (2014) Big Everidge Hollow 1670–1940 28 0.111 0

Schuler and McClain (2003) Pike Knob 1850–1969 12 0.005 0

Shumway and others (2001) Big Savage Mtn. 1600–1949 35 0.105 0

Note: the Trend column indicates sites for which the DFI shows a statistically significant rise (+), a 

statistically significant decline (−), or no statistically significant trend (0).

CRX = Cooper Ridge “Near” site; CRT = Cooper Ridge “Far” site.

42 Chapter 4. Appalachian Fire History as Reconstructed from Fire-Scarred Trees

The DFI has been reported for several fire history sites (Aldrich 

and others 2014, Flatley and others 2013, Hoss and others 

2008). Additionally, for this synthesis we have calculated DFI 

for the remaining Appalachian fire history sites based on scar 

and recording tree data obtained from the published fire charts. 

Where studies do not distinguish recording versus non-recording 

years, we had to assume that every sampled tree was recording 

continuously for every year of its life. This assumption is 

unrealistic, and therefore the calculations for these cases will 

be biased toward less fire activity than actually occurred. After 

obtaining DFI for all the fire history sites, we regressed DFI 

against time for the pre-exclusion era to look for long-term trends 

in fire frequency before the exclusion era (table 4.04; fig. 4.17). 

If fire frequency rose over the course of European settlement and 

industrialization, positive relationships should emerge.

The DFI analyses suggest two general conclusions. First, fire 

frequency declined sharply with the advent of fire exclusion and 

remained low thereafter (fig. 4.17). Second, little evidence exists 

for a peak in fire frequency during the industrial phase or for a 

long-term rise in fire frequency, as positive trends are lacking for 

most fire history sites (table 4.04). Only in one area, the northern 

Appalachian Plateau in Pennsylvania, did fire frequency exhibit 

a positive trend across multiple study sites [fig. 4.17B and Brose 
1500

1540

1580

1620

1660

1700

1740

17801820

1860

1900

1940

1980

2020

Fire frequency

Year

Fire History of the Appalachian Region: A Review and Synthesis 43

Figure 4.18—A revised conceptual model of fire history for Appalachian 

landscapes covered with flammable vegetation such oak- and pine-dominated 

forests. Following observed patterns of decadal fire index (DFI), the model 

portrays decadal variability in fire frequency prior to the fire-exclusion era but 

no long-term change until the fire-exclusion era. Notably, the model does not 

depict an anomalous rise in fire frequency during the industrial period of the 

late 19th and early 20th centuries.

and others (2013, 2015) sites in table 4.04]. Nearly all the other 

sites were characterized by temporal trends resembling those 

shown in fig. 4.17A—fire frequency remained fairly constant 

over the various land-use phases before exclusion but varied 

around this level from decade to decade.

The long-term stability of fire activity differs from interpretations 

found in some fire history papers. For example, McEwan and 

others (2014) stated that for a site in eastern Kentucky they 

“detected many fewer fires in the 1700s and early 1800s than in 

the period from 1875 to 1950. Studies conducted in deciduous 

forests that have access to fire scars from prior to 1850 largely 

support these findings” (2014: 318). The problem with such an 

interpretation, as McEwan and others acknowledge, is that sample 

size varies temporally—the early part of the record is represented 

by fewer fire-scarred trees than the later part. Because trees are 

imperfect recorders of fire history, the change in sample size will 

inevitably yield an apparent change in fire interval even if no such 

change actually occurred. Only by compensating for the varying 

sample size, as through the decadal fire index used here, can fire 

history be represented more accurately.

In light of the analyses reported here, it appears that previous 

conceptual models of Appalachian fire history should be revised, 

at least for areas covered primarily with oak- and pine-dominated 

forests and other flammable vegetation such as savannas 

(fig. 4.18). Fires burned frequently during all land-use phases 

except fire exclusion. Burning was common even on landscapes 

with little human presence, as seen where aboriginal depopulation 

preceded European settlement. Frequent burning would have 

required some minimum density of ignitions, but the required 

density might have been quite low if fires grew large enough 

on the unfragmented landscapes of the past to spread regularly 

through many forested stands and grasslands, including the fire 

history study sites that have been sampled.

As for the industrial logging era, some fires may have been 

unusually severe owing to heavy fuel loads, but the intervals 

between fires were not atypical. This finding possibly indicates 

that fire intervals were controlled not by ignition density or by 

the amount of heavy fuels but by the recovery of fine fuels that 

carried fires over the landscape. A scarcity of such fuels likely 

explains the anomalous rising trend in fire frequency on the 

Appalachian Plateau of Pennsylvania (fig. 4.17B). At these study 

sites, Brose and others (2013, 2015) sampled fire-scarred red 

pines and pitch pines on dry upper slopes that were surrounded 

in the past by eastern hemlock–white pine–northern hardwood 

forest. This mesophytic vegetation would not have carried fire as 

readily as the oak- and pine-dominated forests to the south, and 

therefore fires apparently were unable to burn frequently until the 

advent of European settlement and logging in the 19th century.

The picture that seems to emerge from the multicentury firescar studies conducted in oak- and pine-dominated landscapes 

is that ignitions occurred at sufficient densities to maintain 

stable fire regimes regardless of human land use. Therefore, the 

short fire intervals reported in table 4.02 appear to represent 

a stable, multicentury fire regime, not one that applies only 

to a brief industrial episode. Frequent burning extended from 

presettlement/early European settlement until it was ended 

by fire prevention and suppression in the 20th century. This 

interpretation can be made with greatest confidence for the 

parts of Appalachia covered by the longest fire histories—the 

core of the region encompassing the Blue Ridge province and 

the Ridge and Valley province of Tennessee, North Carolina, 

and Virginia, as well as the eastern Appalachian Plateau in 

Kentucky and Maryland. These areas have the greatest extent 

of publicly managed land in the region, and therefore they offer 

the best opportunities to reintroduce fire at levels that influenced 

vegetation development for at least two or three centuries before 

the era of fire exclusion.

FIRE–CLIMATE RELATIONS

Although the influence of human land use on past fire 

regimes has received much attention in the Eastern United States, 

climatic variability can also affect burning, as demonstrated 

by numerous fire history studies in the American West 

(e.g., Grissino-Mayer and others 2004, Heyerdahl and others 

2002, Kitzberger and others 2007, Veblen and others 2000) and 

by fire–climate relationships observed in the Appalachians today 

(chapter 2). Because fires currently burn more frequently during 

dry years than at other times, it is reasonable to hypothesize that a 

similar relationship existed in the past.

Evidence for such a relationship is limited, however. The authors 

of fire-scar studies reported in this chapter have compared fire 

and drought for 20 study sites (in some studies, the analyses were 

combined across multiple sites) where drought was characterized 

using the Palmer Drought Severity Index, or PDSI (Palmer 1965). 

Negative PDSI indicates dry conditions, but fire is not strongly 

linked to negative PDSI at any Appalachian sites except for Mill 
Lag from fire year

1.0

0.8

0.6

0.4

0.2

0.0

-0.2

-0.4

-0.6

-0.8

-1.0

1.0

0.8

0.6

0.4

0.2

0.0

-0.2

-0.4

-0.6

-0.8

-1.0

Mean PDSI

SEA for all seasons,

Reddish Knob, VA 95% Cl 99% Cl

-6 -5 -4 -3 -2 -1 0

44 Chapter 4. Appalachian Fire History as Reconstructed from Fire-Scarred Trees

Mountain and Reddish Knob on the George Washington National 

Forest, Virginia (Aldrich and others 2014). The climate relations 

for these two sites, one of which is indicated in fig. 4.19, were 

established using superposed epoch analysis (SEA), a technique 

based on averaging annual PDSI values for all fire years to look 

for anomalously high or low values during or before the year 

of fire (Grissino-Mayer 2001b, 2016). A few other sites exhibit 

weak evidence for a similar relationship, but in general, most 

data indicate that fire showed little response to interannual 

climate variations.

The weak response to climate may stem from the overwhelming 

influence of human activities (McEwan and others 2007). For 

example, people could have intentionally avoided burning in 

drought years and instead targeted favorable burning windows 

during normal or even wet years, with the result that fire activity 

was not strongly tied to dry years. If this interpretation is correct, 

the strong climate relationship for the two sites in George 

Washington National Forest may reflect their remoteness from 

human influences (Aldrich and others 2014). To tease out the 

climate influence for sites with a stronger human impact would 

require a different analysis technique (Grissino-Mayer 2016). 

One promising approach is bivariate event analysis (BEA), 

which can be used to determine whether fire tends to occur in 

synchronicity with a climate process. Grissino-Mayer (2016) 

found that for the Brush Mountain fire history site, fires were 

synchronous with positive phases of the El Niño–Southern 

Oscillation and the North Atlantic Oscillation. These conditions 

bring relatively warm, dry winters that would facilitate the drying 

of fuels and would therefore increase the likelihood of extensive 

burning during the subsequent spring.

At the time scale of seasons, the annual climate cycle seems to 

have controlled fire occurrence in the past. Dormant-position 

scars prevail at most study sites (table 4.05), making up 71.5 

percent of the scars, on average. The dominance of dormantposition scars is consistent with fire seasonality today, where fire 

activity peaks during spring and fall (chapter 2). These seasons 

generally present the best opportunities for widespread burning 

on humid landscapes dominated by deciduous forest—humidity 

is lower than usual, wind is strong, and no canopy is present 

to block the wind and sun from drying the fine fuels on the 

forest floor.

Earlywood scars also make up a substantial proportion (mean 

24.6 percent) of the total at some locations, especially the Ridge 

and Valley province, but latewood scars are more rare (mean 

8.3 percent) (table 4.05). Because earlywood scars formed in 

spring, they may be explained by the same springtime weather 

that accounts for the dormant scars. In fact, some individual fires 

are recorded by dormant-position scars on certain trees and by 

earlywood scars on others (Aldrich and others 2010), suggesting 

that the fire occurred just as trees were ending their dormancy. Of 

the dormant scars formed in spring (instead of fall), they probably 

belong with earlywood scars in a single, multimonth spring fire 

season, as seen at present (chapter 2). Any further specifications 

as to the months or portions of months that correspond with 

dormant versus earlywood scars would require greater knowledge 

about tree-ring phenology. This topic deserves future research, 

including investigations into how phenology varies with respect 

to latitude, terrain, and climate change. 

Figure 4.19—Results of superposed epoch analysis (SEA) for the Reddish Knob study site, George 

Washington National Forest, Virginia (Aldrich and others 2014). SEA was used to determine if fires were 

associated with anomalous Palmer Drought Severity Index (PDSI) during the year of fire or during the six 

preceding years. Fires at Reddish Knob were associated with drought (indicated as a negative PDSI value) 

during the year of fire. Asterisks indicate a statistically significant association. CI = confidence interval.
Table 4.05—Fire-scar seasonality for each study site, calculated as 

the percentage of all scars at the site for which seasonality could 

be determined

Source Site name

Season

Dormant Early Late

------------percent------------

Aldrich and others (2010, 2014) Kelley Mtn. 86.1 13.9 0

Mill Mtn. 89.6 9.7 0.7

Reddish Knob 56.5 37.1 6.4

Armbrister (2002) GSMNP >50 — —

Brose and others (2013, 2015) Long Br. Hill 100 0 0

Slate Run 91.3 8.7 0

Upper Dry Run 50 50 0

DeWeese (2007) Brush Mtn. 84 14.2 1.8

Griffith Knob 29.7 67.6 2.7

L. Walker Mtn. 35.1 60.8 4.1

North Mtn. 76.3 22.4 1.3

Feathers (2010) CRX 91.7 8.3

CRT 87 13

Flatley and others (2013) House Mtn. 75.4 23.7 0.9

Licklog Rdg. 90.6 9 0.4

Linville Mtn. 75.2 24.8 0

Hessl and others (2011) Pike Knob 16 56 28

12 53 35

89 11 0

Hoss and others (2008) Peters Mtn. 93.6 1.8 4.6

Hutchinson and others (2008) All sites combined 85.7 14.3 0

LaForest (2012) Gold Mine 61.7 38.3

Rabbit Creek 84.1 15.9

Pine Mtn. 83.8 16.2

Maxwell and Hicks (2010) Endless Wall 100 0 0

McEwan and others (2007) All sites combined 84 13 3

Shumway and others (2001) Big Savage Mtn. 91 2.9 6.4

Sutherland and others (1997) REMA 69 25 6

Note: For two studies (Feathers 2010 and LaForest 2012), the dormant- and early-season scars 

were reported together, and we have indicated these combined-season values by placing them 

between the Dormant and Early columns. 

— = no data reported. 

GSMNP = Great Smoky Mountains National Park; CRX = Cooper Ridge “Near” site; CRT = Cooper 

Ridge “Far” site; REMA = Raccoon Ecological Management Area.

Fire History of the Appalachian Region: A Review and Synthesis 45
46 Chapter 4. Appalachian Fire History as Reconstructed from Fire-Scarred Trees

IGNITION SOURCE: PEOPLE OR LIGHTNING?

Fire seasonality links to the question of ignition source—

did people start most fires in the past as they do today? Or 

did lightning play a greater role when landscapes were less 

fragmented and fires could spread more readily from sparse 

ignition points than at present? Fire scars potentially offer 

insights into these questions (Allen 2002). In general, the 

preponderance of dormant scars matches the seasonality of 

anthropogenic fires today and therefore suggests that humans 

also set most fires in the past. On the other hand, many of the 

dormant-season scars probably formed as trees were ending 

dormancy in spring, as discussed above, and therefore could 

reflect lightning-ignited fires.

A further clue would be provided if scar seasonality varied over 

time—for example, if the proportion of dormant-season scars 

increased as human land use intensified over the course of White 

settlement and industrialization. However, no discernible or 

consistent shift in seasonality emerges among fire history sites 

in the Ridge and Valley or Blue Ridge provinces of Virginia and 

Tennessee (Aldrich and others 2014, DeWeese 2007, LaForest 

2012) or in the Appalachian Plateau of Maryland or Pennsylvania 

(Brose and others 2013, Shumway and others 2001). The 

constancy in scar seasonality may indicate that people remained 

the dominant ignition source, even during periods with little 

human presence in the 17th and 18th centuries. On the other 

hand, it is conceivable that lightning ignitions compensated for 

anthropogenic ignitions during periods of low human activity.

Some western U.S. researchers have attempted to discern the 

relative importance of lightning and anthropogenic ignitions by 

looking for temporal changes in fire frequency that coincided 

with known changes in human land use. Where these changes 

coincided, they may indicate human control over ignitions (Allen 

2002). In the Appalachians, however, temporal changes in fire 

frequency were generally absent (e.g., figs. 4.17A, 4.18), possibly 

indicating a compensating role of lightning ignitions, at least in 

some places. Scar seasonality is not inconsistent with lightning 

ignitions because the lightning fire season overlaps the spring 

anthropogenic fire season.

Therefore, fire scars do not fully answer the question of ignition 

source. They record only the occurrence of a fire, not its cause. 

A reasonable guess is that human-ignited fires predominated in 

the past as at present, but that lightning-ignited fires contributed 

more strongly than at present because of open vegetation and 

continuous fine fuels that would have favored the ignition and 

spread of these fires (see chapter 2). Lightning was probably an 

important ignition source in areas where growing-season scars 

are most abundant and lightning ignitions remain fairly common 

today (e.g., parts of the Blue Ridge Mountains and the Ridge and 

Valley province). These areas also have a greater extent of fireadapted vegetation than the Appalachian Plateau, including oak 

and pine forests with endemic plants that display fire adaptations 

such as thick, fire-resistant bark, serotinous cones, and smoke/

heat-induced germination. These adaptations are thought to imply 

a long history of lightning-ignited fires (Frost 1998, Noss 2012).

SPATIAL PATTERNS OF FIRE

Geographical Variations in Fire Frequency 

Across the Appalachian Region

Regardless of ignition source, an important consideration 

is whether fire intervals varied geographically across the 

Appalachian region, given the differences in climate, vegetation, 

terrain, and land use. This question is especially pertinent to fire 

management. Because resource managers implement prescribed 

burning on landscapes that lack detailed fire history studies, they 

need to know whether the published, site-specific fire histories 

conform to a general spatial pattern that reflects predictable 

relationships with climate or other factors.

In one attempt to delineate spatial patterns of fire, Frost (1998) 

mapped presettlement fire regimes for the entire coterminous 

United States. He obtained fire return intervals from fire scar 

studies or estimated them from vegetation characteristics, and 

then interpreted their relationships with terrain. Terrain dictates 

the size of fire compartments—large compartments burn more 

frequently than small ones, all else equal, because few ignitions 

are needed to burn an entire landscape that contains large fire 

compartments. Hence the Gulf and Atlantic Coastal Plains, with 

their vast expanses of uninterrupted uplands, are predicted to 

have had short fire intervals, whereas the broken Appalachian 

terrain would have seen longer intervals. 

Frost (1998) suggested a pronounced geography of fire across the 

Appalachian region (fig. 4.20), with longest fire intervals (26–100 

years) on the central and eastern Appalachian Plateau and shortest 

intervals (4–6 years) on the western Appalachian Plateau and 

parts of the Blue Ridge Mountains. Fairly short intervals (7–12 

years) are also predicted for sections of the Ridge and Valley 

province and for the subdued terrain of the Piedmont east of the 

mountains. These estimates apply at a coarse resolution. That is, 

they lump an entire region into a single fire regime class based on 

the MFI for the most flammable parts of a landscape.
Frost’s (1998) estimated fire

frequency regimes

1–3 years

4–6 years

7–12 years

13–25 years

26–100 years

100–500+ years

Figure 4.20—Frost’s (1998) estimates of presettlement fire frequency in the Appalachian Mountains and surrounding 

areas. Frequency is highest along the coastal plain and interior lowlands, and lowest in the interior of the Appalachian 

region. Within the Appalachian region, the highest frequencies are along the eastern and western edges.

Fire History of the Appalachian Region: A Review and Synthesis 47
48 Chapter 4. Appalachian Fire History as Reconstructed from Fire-Scarred Trees

In a promising attempt to define a general, predictive model of 

past fire intervals at higher spatial resolution, Guyette and others 

(2012) developed a regression model that predicts pre-exclusion 

(1650–1850) MFI based on fundamental chemical processes 

controlled by climate in equation (2):

MFI = 0.232 + (2.62 × 10-28 × ARterm) + (52 × PTrc ) (2)

where MFI is the composite MFI in years for a 247-acre 

(1- km2) area. In other words, the model predicts the interval 

at which fires will burn at least part of a 247-acre area. ARterm

represents a separate equation that accounts for the effects 

of physical chemistry (reaction rate and requirements for 

ignition) as controlled by temperature and precipitation. It also 

includes oxygen concentration as a function of elevation. PTrc

represents fuel amount and moisture, based on precipitation 

and temperature. Because it is based on fundamental chemical 

processes, this model is robust in that it can be applied to any 

location in the United States (or elsewhere). The model was 

calibrated by using composite MFI for 170 fire history sites 

spanning a wide range of climates across North America, 

predominantly from the West but also from the East, including 

one or two locations in the Appalachian region. In calibrating to 

MFI, the model translates chemical reaction rate to likelihood of 

fire ignition and spread. The model predictions explain 80 percent 

of the variability in independent validation datasets.

To examine model predictions for the Appalachian region, 

we reproduced and mapped the predictions by using a 247-

acre (1-km2) grid for the region. The resultant map (fig. 4.21) 

suggests pronounced geographical variations that generally 

correspond to the patterns identified by Frost (1998): composite 

MFI of 6–10 years for the warmest, driest valleys, but 50 years or 

more for the cool, wet highlands of the Appalachian Plateau and 

Blue Ridge Mountains.

This predicted pattern generally corresponds with empirical 

estimates from the fire history studies discussed in this report. 

Study sites in the Blue Ridge Mountains and the Ridge and 

Valley province had short composite MFI (fig. 4.22, large 

circles), as did sites along the western edge of the Appalachian 

Plateau. The eastern section of the Plateau had longer intervals 

(small circles). It should be noted that this map includes both 

pine-based and oak-based fire histories, and that oak provides 

less reliable fire histories than pine. Therefore, to examine 

spatial patterns based solely on the best records, we mapped the 

pine-based studies alone (fig. 4.23). The resultant map excludes 

most of the Appalachian Plateau studies, but the pattern appears 

consistent with the previously mapped pattern in showing less 

frequent fire on the handful of Plateau sites than in the two 

provinces to the east.

Spatial patterns of MFI may also be distorted by the large 

differences in sample size among studies, and we therefore 

complemented the composite MFI maps by mapping two 

additional fire-frequency estimates that are insensitive to sample 

size: point MFI and the average decadal fire index for each site. 

However, both suffer from the recorder year problem, which 

means that fire frequency may appear comparatively subdued 

at sites for which we estimated the values from published fire 

charts that do not distinguish between recording and nonrecording fire intervals (see table 4.02 for the sites where this 

consideration applies).

The mapped patterns (figs. 4.24, 4.25) are similar to those for 

composite MFI. The general pattern seems robust, therefore 

suggesting that an actual fire-frequency gradient existed in 

which fire activity was greatest in the Ridge and Valley province, 

the Blue Ridge Mountains, and possibly the western edge of 

the plateau. Fire was less common on the eastern Appalachian 

Plateau. The general agreement of this pattern with that predicted 

from the Guyette and others (2012) model suggests that past fire 

regimes were strongly influenced by the overall climate of a site 

and the resulting vegetation, even if—as discussed in the section 

on fire–climate relationships—temporal patterns of burning were 

not sensitive to climatic variations from year to year.

Despite the resemblances between predicted and observed spatial 

patterns, however, the model overestimates composite MFI for 

Appalachian sites. That is, the relative values of MFI correspond 

with predicted variations across the region, but their absolute

values are shorter than predicted. When the observed and 

predicted MFI are compared for the 21 fire chronologies covering 

the preindustrial era (fig. 4.26), the predicted intervals are found 

to be 4.2 times longer, on average, than the observed intervals. 

Predicted MFI was near the observed interval for only two sites, 

both on the Appalachian Plateau. The other three plateau sites 

also show a reasonable correspondence in that predictions and 
4.00

6.00

8.00

10.00

12.00

14.00

16.00

18.00

20.00

22.00

24.00

26.00

28.00

Predicted MFI

Guyette and others (2012)

26.00

28.00

30.00

35.00

40.00

45.00

50.00

75.00

100.00

125.00

150.00

175.00

191.68

Figure 4.21—Pre-exclusion composite mean fire interval (MFI) predicted for 247-acre (1-km2) grid cells by 

using the regression model of Guyette and others (2012). Fire frequency is highest on the southern coastal 

plain and decreases toward the cool, moist climates at higher latitudes and elevations.

Fire History of the Appalachian Region: A Review and Synthesis 49
Appalachian Plateau

Ridge and Valley

Blue Ridge

Piedmont

Physiographic province

1.9–3.9

4.0–5.9

6.0–7.9

8.0–9.9

10.0–11.9

12.0–19.5

Composite MFI

Figure 4.22—Composite mean fire interval (MFI) for all reviewed fire-scar studies in the Appalachian 

region. Fire intervals are represented using red graduated symbols, with larger symbols indicating shorter fire 

intervals. Sources are listed adjacent to study sites. Composite MFI is relatively short along the Ridge and 

Valley province and the Blue Ridge Mountains, short to moderate on the western Appalachian Plateau, and 

long on the eastern Appalachian Plateau.

50 Chapter 4. Appalachian Fire History as Reconstructed from Fire-Scarred Trees
Appalachian Plateau

Ridge and Valley

Blue Ridge

Piedmont

Physiographic province

1.9–3.9

4.0–5.9

6.0–7.9

8.0–9.9

10.0–11.9

12.0–19.5

Composite MFI

Fire History of the Appalachian Region: A Review and Synthesis 51

Figure 4.23—Composite mean fire interval (MFI) for all reviewed fire history studies based on fire-scarred 

pines in the Appalachian region. Fire intervals are represented using red graduated symbols, with larger 

symbols indicating shorter fire intervals. In general, composite MFI is consistent across the central and 

southern Appalachian region. The longest intervals are in the northern section of the Appalachian Plateau in 

Pennsylvania. Sources are listed adjacent to study sites.
Appalachian Plateau

Ridge and Valley

Blue Ridge

Piedmont

Physiographic province

5.3–8.9

9.0–12.9

13.0–16.9

17.0–20.9

21.0–49.8

Point MFI

Figure 4.24—Point mean fire interval (MFI) for all reviewed fire-scar studies in the Appalachian region. Fire 

intervals are represented using red graduated symbols, with larger symbols indicating shorter fire intervals. 

Point MFI is relatively short along the Ridge and Valley province, the Blue Ridge Mountains, and the western 

Appalachian Plateau. Point MFI is long on the eastern Appalachian Plateau. Sources are listed adjacent to 

study sites. 

52 Chapter 4. Appalachian Fire History as Reconstructed from Fire-Scarred Trees
Appalachian Plateau

Ridge and Valley

Blue Ridge

Piedmont

Physiographic province

0.00–0.19

0.20–0.39

0.40–0.59

0.60–0.79

0.80–0.90

Average DFI

Figure 4.25—Decadal fire index (DFI) averaged across all pre-exclusion decades for all reviewed fire-scar 

studies in the Appalachian region. Shorter intervals are represented with gradually larger red circles. DFI is 

relatively short along the Ridge and Valley province and the Blue Ridge Mountains, short to long on the western 

Appalachian Plateau, and long on the eastern Appalachian Plateau. Sources are listed adjacent to study sites. 

Fire History of the Appalachian Region: A Review and Synthesis 53
0 5 10 15 20 25 30 35

0

35

30

25

20

15

10

5

0

Observed MFI

Predicted MFI

AP site RV site BR site

54 Chapter 4. Appalachian Fire History as Reconstructed from Fire-Scarred Trees

observations rise in concert, but model predictions are poor 

for sites in the Ridge and Valley province and the Blue Ridge 

Mountains, where the observed MFI falls within a narrow range 

of about 2–6 years even at relatively cool, moist, mid-elevation 

sites with much longer predicted intervals.

The discrepancies may reflect several factors. First, the model 

omits variables, such as ignition frequency and land use, that 

could have affected fire frequency. Second, it distills temporal 

variations in climate to the annual mean and reduces spatial 

variations in climate to a 247-acre resolution. However, these 

simplifying assumptions would not seem to bias MFI predictions 

systematically toward overestimates of fire interval length. 

The overestimates likely reflect additional factors that are not 

amenable to modeling. Two such factors are spatial contingencies 

and positive feedbacks.

Spatial contingencies arise because the area surrounding a point 

can play as great a role as conditions at the point itself (Phillips 

2001). Contingencies weaken the predictability of many earthsurface phenomena, from soil development (Phillips 2001) to fire 

occurrence (Baker 2003). In the case of fire frequency, the long, 

high ridges in the Ridge and Valley province and the Blue Ridge 

Mountains connect to lower slopes and valleys with warmer and 

drier climates that make them susceptible to fire. Fires may have 

spread widely from more flammable to less flammable sites, 

elevating fire frequency to higher levels than would be expected 

from site conditions alone. Examining the location of fire history 

study sites in these two provinces (e.g., fig. 4.27) reveals the 

Figure 4.26—Scatterplot demonstrating the relationship between the observed 

mean fire intervals (MFI) at Appalachian study sites and the MFI predicted 

for those sites using the regression model of Guyette and others (2012). If 

observations matched the predictions perfectly, all the points would fall along 

the diagonal 1:1 line. Where points fall below the line, the model overestimated 

MFI (i.e., the model predicted less frequent fire than was observed). AP = 

Appalachian Plateau, RV = Ridge and Valley, BR = Blue Ridge.

proximity of the sites to broad, more fire-prone lowlands. In 

contrast, the Appalachian Plateau generally has lower relief 

and therefore less juxtaposition of warm, dry and cool, moist 

sites (fig. 4.27). Additionally, the slopes on the plateau do not 

connect to broad, dry valleys as in the other provinces but to 

moist, narrow stream valleys with relatively incombustible 

mesophytic forest.

Positive feedbacks probably also elevated fire frequency. 

Frequent burning would have promoted open forests and 

woodlands with a fairly continuous grass-shrub understory that, 

in turn, enabled fires to grow rapidly to large size (Harrod and 

others 2000). Moreover, the fire-favored oaks and pines shed 

flammable litter that augmented the continuous fuel bed. In 

these ways, contingencies and feedbacks likely amplified the 

basic regional variations in burning (e.g., Appalachian Plateau 

versus Ridge and Valley province) while diminishing the local 

differences between mountain slopes and adjacent lowlands.

The Spread of Fire Through Multiple Stands

The regular occurrence of large fires, fed by continuous fine fuels, 

could have supported frequent burning at individual fire history 

sites even if ignition densities were low, as in areas remote from 

human activities. Actual fire sizes cannot be ascertained from the 

fire-scar data currently available—such estimates would require 

hundreds of fire-scarred trees from many places on a landscape—

but evidence from several study sites indicates that fires spread 

across the landscape to scar trees at some distance from each 

other. On the Appalachian Plateau in Pennsylvania, for example, 

Brose and others (2013) sampled old fire-scarred pitch pine and 

red pine trees scattered for a mile or more along upper slopes. 

Half or more of these pines were sometimes scarred in a single 

year. This synchronous scarring suggests that fires had spread 

along the top of the plateau and backed down into the gorges to 

scar trees on the upper slopes.

Synchronous scarring has also been observed on mountainsides 

in the Ridge and Valley province and the Blue Ridge Mountains 

(Aldrich and others 2010, 2014; Flatley and others 2013). Each 

fire history site included fire-scarred cross-sections collected 

from multiple pine-dominated patches separated by hardwood 

forest (fig. 4.14). Scar synchronicity among the pine stands 

implies that individual fires spread across the mountainsides to 

encompass both the pine-dominated patches and the intervening 

hardwood stands. The frequency of these synchronous fires has 

been estimated by using the MFI for “area-wide” fires, with 

an area-wide fire defined as an event recorded at all stands in a 

study site during a single year (Aldrich and others 2010, Fisher 

and others 1987). The area-wide MFI gives a conservative 

estimate of fire intervals because to calculate it requires matching 

fire dates across multiple stands with small sample sizes. The 

MFI calculations nonetheless yield relatively short intervals 

(table 4.06) and therefore indicate that frequent burning was not 

restricted to the pine stands from which the fire-scarred trees were 

sampled. Rather, fires commonly burned through the oak-pine 

mosaic that covers the mountain slopes of the Ridge and Valley 
Appalachian Plateau – Long Branch Hill, PA

Brose and others (2013, 2015)

Ridge and Valley – Reddish Knob, VA

Aldrich and others (2014)

Blue Ridge – Linville Mountain, NC

Flatley and others (2013)

Elevation data: National Elevation Dataset (30 m)

Fire History of the Appalachian Region: A Review and Synthesis 55

Figure 4.27—Locations of selected fire history sites (represented as black circles) relative to 

predicted mean fire interval (MFI) calculated by using the regression model of Guyette and others 

(2012). The Long Branch Hill sites of Brose and others (2013, 2015) are in close proximity to 

moist stream valleys containing relatively incombustible mesophytic forest, which may help 

explain why the fire intervals are relatively long. The Reddish Knob site of Aldrich and others 

(2014) and the Linville Mountain site of Flatley and others (2013) are in close proximity to broad, 

fire-prone lowlands, which may help explain the shorter fire intervals.

4.63

6.00

8.00

10.00

12.00

14.00

16.00

18.00

20.00

22.00

24.00

26.00

28.00

30.00

35.00

40.00

45.00

50.00

75.00

100.00

125.00

150.00

175.00

185.14

Predicted MFI

Guyette and others (2012)
Table 4.06— Area-wide mean fire interval (MFI) in relation to current (1986–2009) ignition density on the 

National forest ranger districts in which the study sites are located 

Source Site name

Areawide 

MFI

Study 

site 

size

Ignition density 

required to burn 

all stands separately 

in one year

Current 

ignition density 

by ignition source 

on ranger district

Ratio of 

required vs. 

current 

ignition density

years acres fires/M acres/yr fires/M acres/yr

Aldrich and others 

(2010, 2014)

Kelley Mtn. 7.8 230 17,391 All 23.3 747

Humans 13.2 1,319

Lightning 10.1 1,722

Mill Mtn. 17.3 230 17,391 All 10.4 1,670

Humans 7.5 2,317

Lightning 2.9 5,985

Reddish Knob 8.8 120 33,333 All 26.1 1,275

Humans 22.1 1,506

Lightning 4 8,286

Flatley and others 

(2013)

House Mtn. 7.2 25 – – – –

Licklog Ridge 6.5 100 – – – –

Linville Mtn. 9.2 40 50,000 All 58.9 848

Humans 40.8 1,225

Lightning 18.1 2,759

Note: For the two study sites that are not on National forests, we have not included comparisons to current ignition density. 

– = published data inadequate to provide calculation.

56 Chapter 4. Appalachian Fire History as Reconstructed from Fire-Scarred Trees

and the Blue Ridge provinces. These findings suggest that fire 

compartments were large enough to enclose entire mountainsides, 

perhaps stretching along the ridges for several miles.2 These 

compartments probably also extended into adjacent valleys 

because small streams typically flow at a roughly perpendicular 

angle to the northeast-southwest trend of the ridges to join larger 

streams in the valleys. An ignition in a valley could therefore 

burn unimpeded to the mountain, run up the mountain slope, and 

then spread along the middle and upper slopes of the mountain 

where streams are absent or too small to stop the fire.

The Licklog watershed in the Great Smoky Mountains furnishes a 

good illustration of area-wide fires. This is an unlogged drainage 

basin from which 116 fire-scarred pines were sampled at three 

pine stands interspersed among other forest types covering a 

south-facing slope above Licklog Branch (fig. 4.14B). Area-wide 

fires burned across the slope with a MFI of 6.5 years (Flatley 

and others 2013), in the process scarring a few pines that stood 

in an oak stand situated between two adjacent pine stands. The 

fires also spread into the mesophytic cove forest in the valley, at 

least on occasion, as shown by fire-scarred hardwood and eastern 

hemlock trees growing to the edge of Licklog Branch at the base 

of the slope. The entire slope appears to represent a single fire 

compartment, therefore, in which case the unfiltered composite 

2 Personal communication. 2015. Cecil Frost, Consultant, Blue Star Consulting, 

119 Potluck Farm Road, Rougemount, NC 27572.

MFI of 2.2 years (table 4.02) may best approximate the past fire 

interval for the slope. 

These widespread fires contradict recent assertions (e.g., Hart 

and Buchanan 2012, Matlack 2013) that burning was restricted 

to small ribbons of oak–pine forest growing on xeric ridgetops. 

This interpretation apparently reflects a misconception about 

vegetation distribution, namely, that oak- and pine-dominated 

stands are restricted to ridgetops. If that were true, fire histories 

based on oaks or pines might apply only to xeric ridgetops, 

where frequent burning reflected “microclimatic and edaphic 

peculiarities” that distinguished xerophytic oak–pine stands from 

a broader “mesic deciduous forest” that rarely burned (Matlack 

2013). Only in close proximity to aboriginal villages could 

Matlack (2013) envision substantial burning of the prevailing 

mesic deciduous forest. 

Actual conditions on Appalachian landscapes differ greatly from 

such interpretations. First, not all Appalachian fire history sites 

are located near former Native American villages (or those of 

European settlers), yet several sites evidence frequent burning 

even before the widespread European settlement and industrial 

logging of the 19th century (e.g., fig. 4.17A). Second, many fire 

history sites are not located on ridgetops but on mountainsides 
Fire History of the Appalachian Region: A Review and Synthesis 57

covered with an oak-pine mosaic that was swept frequently by 

area-wide fires. Third, in a process known as spotting, wildfires 

may spread across drainages and ridges when sparks or embers 

are carried away from the main fire and ignite fuels downwind. 

Spotting has been observed to ignite patches up to one-half 

mile away in the Appalachian Mountains (see footnote 1). 

These circumstances strongly suggest that in the past, fires 

spread readily through the entire oak–pine complex to influence 

vegetation dynamics across the mountain slopes of the Ridge and 

Valley province and the Blue Ridge Mountains.

An area-wide fire event may perhaps represent separate small 

fires that burned neighboring pine stands synchronously without 

spreading through the intervening hardwood forest. If we 

assumed this were the case, it would mean that fire histories 

represent the pine stands but not the surrounding landscape. 

This is improbable, however. Synchronous small fires could not 

have occurred on the regular basis seen in the area-wide MFI 

calculations because they would have required an unrealistically 

high ignition density. Consider, for example, the four pine stands 

that make up the Reddish Knob fire history site on the George 

Washington National Forest. The ignition of four separate fires 

during the same year within the 120-acre study site would equate 

to 33,333 fires per 1,000,000 acres per year (table 4.06). This 

ignition density is 1,275 times greater than the present ignition 

density for the National forest ranger district on which the site 

is located, based on fire incidence data for 1986–2009 from the 

National Interagency Fire Management Integrated Database 

(Lafon and Quiring 2012, USDA Forest Service 1998). Such 

a high ignition does not seem plausible for a mountain slope 

that was isolated from Native American villages and European 

settlements until the late 18th century (cf. Aldrich and others 

2014). All the more astonishing would have been the ignition of 

so many fires in small pine stands on the side of a ridge with no 

ignitions elsewhere, such as the more accessible valley bottom. 

Nor could lightning have been expected to strike numerous 

individual stands within a single year—that would require 

> 8,000 times the current density of lightning-ignited fires 

(table 4.06). Similar conditions apply to the other study sites 

reported in table 4.06.

The straightforward explanation for frequent area-wide fires is 

that the fires spread across the mountain slope to encompass 

multiple pine and hardwood stands. Exactly how large the fires 

grew is not yet evident from any fire history studies because 

none has been conducted at the scale necessary to make such 

a determination. But we can state confidently that fires were 

common within the entire oak-pine mosaic.

This mosaic is the primary vegetation feature on Appalachian 

ridges within the Ridge and Valley and the Blue Ridge provinces 

(fig. 4.28). It covers approximately 70–75 percent of all the land 

Figure 4.28—Landscape in the Blue Ridge Mountains (James River Face Wilderness, Jefferson National Forest) on which the oak-pine mosaic is prevalent. 
58 Chapter 4. Appalachian Fire History as Reconstructed from Fire-Scarred Trees

area within the George Washington, Jefferson, and northern 

Cherokee National Forests (Medlock 2012; Simon 2011, 2013). 

It also covers between 23 and 53 percent of the Pisgah and 

Nantahala National Forests, respectively (Simon and others 

2005). In all cases, these are conservative estimates of the total 

proportion of pyrogenic vegetation because they exclude lowelevation shortleaf pine–oak, high-elevation red oak, and other 

stand types beyond the immediate vicinity of the mid-elevation 

oak–pine mosaics at the fire history study sites. The inescapable 

conclusion that emerges from the data at hand is that fires burned 

frequently and extensively across the various forest stands that 

cover most of the mountain slopes in the Ridge and Valley 

province and the Blue Ridge Mountains.

CONCLUSIONS AND IMPLICATIONS

A picture of frequent burning emerges from the network of 

fire-scar sites that have been established over the past 15 years. 

This picture is clearest for portions of the Blue Ridge Mountains, 

Ridge and Valley province, and Appalachian Plateau where 

lengthy fire chronologies have been assembled from large 

samples of fire-scarred trees. At these sites, fires occurred 

frequently, from the beginning of the record in the 17th and 18th 

centuries until the advent of fire exclusion in the early to middle 

20th century. 

The reconstructed fire histories show considerable site-to-site 

agreement, especially within a physiographic province. The 

robustness of the results suggests that they provide adequate 

guidance for fire management on the core Federal, State, and 

private conservation lands within the Blue Ridge and the Ridge 

and Valley provinces of eastern Tennessee, northwestern North 

Carolina, and western Virginia. Additionally, the work on 

the Appalachian Plateau of central Pennsylvania is rounding 

out our understanding of fire history in the northern part of 

the study region. When combined with ongoing research in 

the Pennsylvania section of the Ridge and Valley province 

(Marschall and others 2016), these studies have application to 

the extensive State game lands in Pennsylvania.

Other areas are not as well represented by fire history studies, 

including much of the Appalachian Plateau, large sections of the 

southern Blue Ridge Mountains, and the Piedmont. Developing 

fire history studies for these and other underrepresented areas 

would benefit fire management and would also help contextualize 

the results from the more intensively sampled locations. For 

example, did the Piedmont have shorter fire intervals than the 

mountains, as predicted by the models of Frost (1998) and 

Guyette and others (2012)? Answering such questions depends 

on whether an adequate number of fire-scarred trees has 

escaped decay and destruction by the heavy land use that has 

characterized certain areas of the Appalachian region.

Just as important as filling these broad geographic gaps is 

to study fire history more intensively at a landscape scale. 

Recent debate about fire history largely collapses to the issue 

of fire extent on landscapes—were fires restricted to narrow 

ridgetop oak–pine stands, or did they extend broadly across 

the forested mountain slopes? The evidence at hand strongly 

suggests that fires burned through the entire oak–pine mosaic, 

but additional studies are needed to illuminate the full extent of 

individual fires. Doing so would require large samples of old 

fire-scarred trees arrayed in many clusters across a landscape. 

Such clustered sampling has already begun in many of the study 

sites; one or more of these sites could provide the nucleus for an 

expanded study.

Such work is labor intensive and time consuming. It is to be 

expected, therefore, that the expansion of the Appalachian firescar network will proceed at a modest pace, at best. Regardless, 

the studies completed to date have illuminated much that was 

previously unknown about Appalachian fire history. They support 

hypotheses (e.g., Abrams 1992, Day 1953, Lorimer 1984) that 

fire occurred frequently before fire exclusion, and they offer 

invaluable guidance to managers who implement prescribed 

burning to restore a fire regime comparable to that which 

prevailed before fire exclusion.
Fire History of the Appalachian Region: A Review and Synthesis

59

pine stands of the Appalachian Mountains. Frost proposed that 

these stands developed under a “polycyclic” fire regime in which 

most of the pines established under the high light levels that 

followed relatively severe, canopy-opening fires, which burned 

at intervals of approximately 75 years. Lower-severity surface 

fires also swept the stands at short intervals, killing understory 

plants but not the overstory pines (Grissino-Mayer 2016). If 

this polycyclic or mixed-severity model is accurate, tree age 

distributions should reveal distinct age cohorts (Fulé and others 

2003, Jenkins and others 2011).

The second insight to be gained from age structure concerns fire 

effects on vegetation. The current age structure reflects which 

species survived frequent burning in the past and whether less 

fire-resistant species have established under fire exclusion. In 

this type of analysis, age structure is used to infer changes in 

stand composition over time (Aldrich and others 2010, Brose and 

Waldrop 2010, Lafon and Kutac 2003, Waldrop and others 2003). 

It is sometimes augmented with vital information on the current 

stand structure and composition (i.e., percentage of seedlings, 

saplings, and mature trees). In other words, researchers can use 

age structure to evaluate concepts such as the fire-oak hypothesis 

and the mesophication process (Abrams 1992, McEwan and 

others 2011, Nowacki and Abrams 2008). 

FIELD AND LABORATORY METHODS

The standard field approach used in studies of stand age structure 

and species composition is the establishment of plots in which 

all trees are identified to species and cored by using an increment 

borer (Speer 2010). For stands that have also been sampled for 

fire history reconstruction, pairing the fire history information 

with detailed plot-level data clarifies the manner in which 

vegetation responded to past changes in the fire regime (Flatley 

and others 2015).

At each plot, the field crew measures and records stem diameter 

and species identification of all living trees with stem diameters 

exceeding a certain size (commonly 2 inches, or 5 cm, at breast 

height). An increment borer is used to extract cores from these 

trees at their base, where the earliest rings can be captured for age 

structure analysis. As for smaller trees (seedlings and saplings 

INTRODUCTION

Our interest in fire history largely reflects a broader interest 

in vegetation dynamics and disturbances, especially how fire 

influences vegetation and what happens to vegetation when fire 

is withheld from communities that burned frequently in the past. 

Knowledge about these issues has been built from various types 

of research, from witness-tree studies to studies of vegetation 

change after recent burns. Age structure analysis is another 

useful approach for learning about vegetation changes. By 

ageing the trees in a stand through tree-ring analysis, researchers 

obtain a snapshot of tree age distribution at a point in time, and 

this distribution, though static, permits inferences about stand 

dynamics and forest history, including the timing and effects of 

past disturbances (Didion and others 2007, Johnson and others 

1994, LaForest 2012).

With respect to fires, the age structure yields two primary 

insights. The first concerns the fire regime itself, and the second 

concerns the effects of fire on vegetation. Regarding the fire 

regime, if a severe fire kills most or all trees in a stand, the forest 

that regenerates on the site will typically contain a primary age 

cohort that is reflected in a unimodal age distribution among 

the colonizing species. In fact, in a crown fire regime (such as 

is found in some boreal forest landscapes) the age structure is 

the primary data source for reconstructing fire history because 

few trees survive with scars that can be dated (Couillard and 

others 2012, Heinselman 1973, Johnson 1992). Ageing trees in 

different-aged patches over a landscape enables the researcher 

to characterize fire frequency by estimating the fire cycle, or the 

average number of years that would be required for the entire 

landscape to burn (Johnson and others 1999, Romme 1982).

A different situation applies in a fire regime once characterized 

by frequent fires, such as the Appalachian Mountains, where the 

fire interval can be more easily calculated from fire-scarred trees. 

In these fire regimes, the age structure yields information about 

the severity of past fires: were they all low-severity surface burns 

that only killed understory trees and shrubs, or did relatively 

severe fires occasionally open the canopy and permit unimodal 

age cohorts to establish in the stand? The latter scenario has been 

hypothesized by Frost (1998) for the Table Mountain pine–pitch 

Chapter 5. 

Stand Age Structure and What it 

Indicates About Past Fire Regimes and 

Fire Effects on Vegetation
Mean number of pines recruited 

per acre per decade at Reddish Knob, VA

55

50

45

40

35

30

25

20

15

10

5

0

Mean number of recruited 

individuals per acre

55

50

45

40

35

30

25

20

15

10

5

0

Decade

17001720

1740

1760

17801800182018401860188019001920194019601980

2000

60 Chapter 5. Stand Age Structure and What it Indicates About Past Fire Regimes and Fire Effects on Vegetation

with stem diameter < 2 inches), they provide information about 

potential successional trends and are therefore tallied by species, 

but they are not aged because they are too small to core.

Tree cores are stored in small-diameter tubes, such as straws, for 

transportation to the laboratory. After drying, the cores are glued 

into wooden core mounts to be sanded and then dated following 

the same procedures as for fire-scarred cross-sections (chapter 4). 

When dated, each tree is assigned to an age-class bin, typically of 

10 years in length. Finally, the age-class data for all trees in a plot 

or study site are aggregated to create a histogram depicting stand 

age structure.

SYNTHESIS OF AGE STRUCTURE 

ANALYSES IN THE APPALACHIAN REGION

Age Structure Data from the Appalachian Mountains

For this chapter, we synthesize the results of age structure 

analyses from 11 sites with yellow pine or yellow pine–oakdominated stands (Aldrich 2011, DeWeese 2007, Flatley and 

others 2015, LaForest 2012). The yellow pines are the “hard” 

or diploxylon pines that make up the subgenus Pinus within the 

genus Pinus (Price and others 1998). We also synthesize results 

from four sites with oak-dominated stands (Aldrich 2011, Flatley 

and others 2015, Hoss and others 2008). The stands, which were 

sampled using rectangular plots of 0.247 acre (0.1 ha) in area, 

were collocated with fire history studies based on numerous old 

fire-scarred trees in Virginia and Tennessee.

Eight of the yellow pine sites were at middle elevations where 

stands were dominated by Table Mountain pine and pitch pine. 

The remaining three were low-elevation sites in western Great 

Smoky Mountains National Park with stands dominated by 

shortleaf (Pinus echinata), pitch, and Virginia pine (P. virginiana) 

mixed with oaks and white pine. Chestnut oak (Quercus 

montana) dominated the stands at the oak sites with northern 

red oak (Q. rubra), scarlet oak (Q. coccinea), and black oak 

(Q. velutina) also common in some stands.

Fire Severity

The age structure data from Table Mountain pine–pitch pine 

stands (Aldrich 2011, DeWeese 2007, Flatley and others 2015) 

provide support for a fire regime with occasional fires of 

moderate to high severity. Most of the age distributions include 

one or more distinct pine cohorts (e.g., fig. 5.01). However, the 

trees do not fall into strictly even-aged cohorts dating to a single 

decade; rather, they fall into broader peaks spanning two decades 

or more, suggesting that the stands did not recover immediately 

from severe disturbances. 

The lifespans of Table Mountain and pitch pines are too short to 

permit the development of multicentury age structure analyses 

such as would be needed to identify several cohorts and verify 

the operation of a polycyclic fire regime. These pines rarely 

live beyond 200 years (Della-Bianca 1990, Little and Garrett 

1990) but depending on species may live to 300–400 years 

(Eastern OLDLIST 2013). Most of them would have been killed 

at younger ages if crown fires recurred at intervals of about 75 

years, as suggested by Frost (1998). Some lived longer, however, 

as evidenced by old fire-scarred trees that were sampled for fire 

history analyses in and around the plots. Because these firescarred trees were sampled from a larger area beyond the plot 

boundaries, it was possible to obtain enough of them to augment 

the plot-based age structures with remnants of earlier cohorts.

Graphing the establishment dates for these pines indicates 

multiple, distinct cohorts in some locations but not in others 

(fig. 5.02). In the particular case shown in figure 5.02, the 

Figure 5.01—The mean number of pines recruited per acre per decade at the Reddish Knob, 

VA, site (after Aldrich 2011). Data from three pine stands analyzed by Aldrich (2011) are 

combined in this graph. The distinct pine cohorts that date to the late 1800s and early 1900s 

likely were established following relatively severe fires or other disturbances.
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Fire History of the Appalachian Region: A Review and Synthesis 61

Figure 5.02—The number of pith dates by decade for fire-scarred yellow pine 

cross-sections at the House Mountain and Licklog Ridge sites in Tennessee 

and the Linville Mountain site in North Carolina (after Flatley and others 

2013). The pine stands at House Mountain show an uneven-aged distribution 

that indicates the trees were established regularly, whereas Linville Mountain 

stands show distinct cohorts that indicate the trees were established within 

short windows of time, probably after severe fires. The Licklog Ridge pine 

stands also show fairly distinct cohorts, although pine recruitment does not 

appear to have been confined as strongly to short windows of time as at 

Linville Mountain.
62 Chapter 5. Stand Age Structure and What it Indicates About Past Fire Regimes and Fire Effects on Vegetation

uneven-aged structure is from a relatively low-elevation site 

(House Mountain) in the Ridge and Valley province of eastern 

Tennessee. At that site, fire history was reconstructed from 

scarred shortleaf, Table Mountain, and Virginia pines. In contrast, 

the most distinct cohorts were found in higher elevation Table 

Mountain pine–pitch pine stands at Linville Mountain along 

the eastern escarpment of the Blue Ridge in North Carolina 

(Flatley and others 2013). These varying age-structure patterns 

resemble the range of patterns discovered in a plot-based study 

of Table Mountain pine–pitch pine stands in different sections of 

the southern Blue Ridge Mountains (Brose and Waldrop 2006). 

Such variations suggest that disturbance regimes differed among 

pine stands (Brose and Waldrop 2006, Flatley and others 2013), 

with even-aged cohorts emerging where crown fires occurred 

periodically and uneven-aged structures developing where 

smaller gaps were present continuously because of frequent 

burning combined with scattered overstory-tree mortality.

Age structure likely reflects the interplay of fire with other 

disturbances, especially insect outbreaks and storms (Aldrich and 

others 2010, Brose and Waldrop 2006, Flatley and others 2013, 

Lafon and Kutac 2003). Even-aged stands would be particularly 

susceptible to outbreaks of southern pine beetle (Dendroctonus 

frontalis), which would have contributed to large gaps, heavy fuel 

loads, and severe fires that perpetuated the development of dense, 

even-aged cohorts. Such cohorts seem mainly to have developed 

in relatively pure Table Mountain pine–pitch pine stands (e.g., 

Aldrich 2011, Flatley and others 2013), whereas uneven-aged 

pine populations developed in lower-elevation stands containing 

shortleaf or Virginia pine and a sizable hardwood component 

(e.g., Flatley and others 2013, LaForest 2012). More data would 

be needed to confirm this observation, but it is reasonable to 

expect that the presence of hardwood trees would have reduced 

stand susceptibility to large gaps created by severe fires because 

hardwood trees and litter are less flammable than pines. Some 

hardwoods are also less vulnerable to disturbances such as ice 

storms (Lafon and Kutac 2003) and southern pine beetles, for 

which they are not hosts.

The relationship between fire and southern pine beetle is 

undoubtedly more complex than suggested from the brief 

foregoing synopsis. One dimension of the relationship that 

deserves more study is the potential role of fire in immunizing 

pines against beetle infestation. By maintaining relatively 

uncrowded pine stands, frequent burning would have promoted 

tree vigor and thereby enabled the trees to produce the heavy 

resin flows needed to resist beetle attack (Knebel and Wentworth 

2007, Schowalter and others 1981). Moreover, exposure to fire 

appears to stimulate increased resin flow in Appalachian pines 

(Knebel and Wentworth 2007), and this elevated flow can be 

sustained for at least 18 months after the fire. When fires occurred 

at short intervals in the past, they likely abetted the resistance of 

pine stands to beetle outbreaks.

Age structure data reveal less about fire regimes of oak stands 

than pine stands in the Appalachian region. Only four study sites 

provide both age structure and fire history information (Aldrich 

2011, Flatley and others 2015, Hoss and others 2008), and at 

three of the sites the oak stands appear to have been logged. Each 

of these logged stands is dominated by a large cohort of oaks and/

or other species that were established at about the time of the last 

major fire. These fires coincided with logging, however, which 

suggests that a combination of fire and logging probably fostered 

the establishment of the dominant tree cohort.

To understand the pre-logging fire regime of oak forests requires 

data from unlogged stands. The best such information is from the 

Licklog Branch watershed in Great Smoky Mountains National 

Park, where a detailed fire history reconstruction indicates that 

fires occurred frequently until 1916, the date of the last major 

fire (> 25 percent of trees scarred; Flatley and others 2013). 

Here, the age structure of chestnut oak stands (fig. 5.03; Flatley 

and others 2015) reveals that oaks established through the 18th, 

19th, and early 20th centuries, and it suggests that the moderatesized gaps needed for oak regeneration were present on a regular 

basis. Whether these gaps were created by fires, storms, or other 

events—or from a combination of disturbance agents—cannot 

be determined from the age structure. Regardless, the unevenaged oak distribution from Licklog Branch watershed indicates 

that the stands were not subjected to catastrophic mortality from 

fires or other events, even while the intermixed pine stands were 

occasionally burned more severely, as indicated by the lack of old 

pines in the plots and by the unimodal pine cohorts documented 

by the fire-scarred cross-sections (fig. 5.02). Most likely, fires 

burned fairly mildly through the hardwoods but sometimes 

flared into the crowns as they passed into the pine stands. This 

interpretation, of varying fire severity across the landscape, 

is supported by a remote-sensing study of a recent wildfire in 

Linville Gorge, North Carolina, where pine stands burned more 

severely than other forest types on the landscape (Wimberly and 

Reilly 2007).

Tree Establishment Under Changing Fire Regimes

Age structure analyses indicate that yellow pines and oaks 

recruited under the frequent burning of the pre-exclusion era, 

whereas a more diverse mix of species became established under 

fire exclusion (Aldrich 2011, DeWeese 2007, Flatley and others 

2015, Hoss and others 2008, LaForest 2012) (e.g., fig. 5.03). 

To synthesize the results from multiple sites, we combined age 

structure data from all studies by aggregating the trees into three 

groups: yellow pines, oaks, and others. Next, for each species 

group, we stacked the decadal age bins from all study sites so 

as to align them by their first decade of fire exclusion. This 

alignment was necessary because effective fire exclusion did not 

occur synchronously among sites. For each study site, therefore, 

we designated the decade of the last major fire as decade 0.
Mean number of all species recruited 

per acre per decade at Licklog Ridge, TN

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Fire History of the Appalachian Region: A Review and Synthesis 63

Figure 5.03—The mean number of all tree species recruited per acre per decade in the chestnut oak stands at the 

Licklog Ridge site in Tennessee (based on data from Flatley and others 2013). The “other” species include various 

species aside from oaks and pines. The oaks were established regularly under the regime of frequent burning, whereas 

the other tree species were primarily recruited during the fire exclusion period (after c. 1910–1930).

When summarized in this manner, the establishment dates for 

yellow pine stands indicate relatively abundant recruitment 

of yellow pines during the pre-exclusion era (i.e., decades 

designated by negative numbers in fig. 5.04A). They also show 

that a pulse of yellow pine establishment coincided with the 

cessation of frequent burning (decades 0–3). This establishment 

pulse likely reflects favorable tree recruitment opportunities 

in the open conditions that had been maintained in the forest 

understories by frequent burning in the past. Once fire was 

excluded and no longer threatening the pine seedlings, they 

recruited in great abundance (cf. Brose and Waldrop 2006). 

This recruitment declined after a few decades, however, as the 

stands grew more crowded. Yellow pines are also present in oakdominated stands (fig. 5.04B) in low numbers.

Oak trees maintained populations within both pine- and oakdominated stands during the pre-exclusion period (fig. 5.04C, D). 

Small oaks were probably top-killed repeatedly by fires but 

would have persisted by resprouting after each fire, developing 

large roots, and then eventually bolting to take advantage of an 

anomalously long fire interval (Brose and others 2014). By the 

time of the next fire, some of these stems would have attained a 

large enough size to survive the fire and continue growing.

Oak sprouts flourished at the beginning of the fire exclusion era. 

With fire absent, a large cohort of sprouts became established 

immediately in decades 0–1, producing coppice-like growths 

of chestnut oak that can be observed in many stands today. This 

pulse of oak establishment must have rapidly depleted the oak 

sprouts, leaving few oaks to recruit in subsequent decades. The 

paucity of oaks originating after decade 3 suggests that the stands 

have become too dense and shaded for oak seedlings or sprouts 

to survive.

Other tree species, which include a wide range of species from 

hickories (Carya spp.) to eastern hemlock (Tsuga canadensis), 

are not well represented among the trees established before fire 

exclusion (figs. 5.04E, F). A few trees of pre-exclusion origin are 

present, but the age-structure histograms drop off sharply back in 

time. This drop-off suggests that “other” species sometimes were 

established under the regime of frequent burning but survived 

only a few decades before being winnowed out by the relentless 

fires. Fire exclusion brought a momentous shift, however. 

This shift is manifested as a strong peak in the age-structure 

histogram at decade 0, which is followed by a moderate level of 

establishment for the next several decades. The absence of fire 

has enabled this suite of species to thrive.
Mean number of yellow pine individuals per acre 

in oak stands per decade relative to fire suppression

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in pine stands per decade relative to fire suppression

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(A) (B)

(C) (D)

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64 Chapter 5. Stand Age Structure and What it Indicates About Past Fire Regimes and Fire Effects on Vegetation

Figure 5.04—(A) The mean number of yellow pines recruited per acre per decade relative to the beginning of fire exclusion in yellow pine-dominated stands in all 

reviewed studies. Decade “0” refers to the decade in which the last major fire occurred. Decades with negative values represent decades prior to fire exclusion, and 

those with positive values represent decades after fire exclusion began. (B) The mean number of yellow pines recruited per acre per decade relative to the beginning of 

fire exclusion in oak-dominated stands in all reviewed studies. (C) The mean number of oaks recruited per acre per decade relative to the beginning of fire exclusion 

in yellow pine-dominated stands in all reviewed studies. (D) The mean number of oaks recruited per acre per decade relative to the beginning of fire exclusion in oakdominated stands in all reviewed studies. (E) The mean number of individuals of other species recruited per acre per decade relative to the beginning of fire exclusion 

in yellow pine-dominated stands in all reviewed studies. (F) The mean number of individuals of other species recruited per acre per decade relative to the decade of fire 

exclusion in oak-dominated stands in all reviewed studies. In general, pine and oak species had established under frequent burning, showed a pulse of establishment in 

the first few decades of fire exclusion, and failed to establish thereafter. The other species, in contrast, mostly were established during the era of fire exclusion.
Figure 5.05—White pine trees growing on talus with discontinuous fuel bed of pine needles. (photo by Steven Q. Croy)

Fire History of the Appalachian Region: A Review and Synthesis 65

Given the diverse ecological requirements of the “other” species, 

their age structure histograms likely reflect multiple recruitment 

modes and fire effects. Under frequent burning, relatively firetolerant hardwoods such as hickories and blackgum probably 

maintained a small presence through repeated sprouting, 

similar to the oaks. Others, such as red maple and white pine, 

probably cast their seeds continually into the pine and oak 

stands without avail. They could not establish there as long as 

fires recurred every few years. When this pressure was relaxed, 

however, seedlings of many species became established, and 

stand composition began shifting toward a more diverse tree 

assemblage. Today, most of the stands remain dominated by 

yellow pines and oaks, but their understories are thick with other 

species that are emerging into the overstory and replacing the 

dominant trees as they die.

Frequent surface burning, therefore, would have played a filtering 

role in species composition (McEwan and others 2014). Even 

though many tree species must have dispersed seeds onto the 

mountain slopes, few of their seedlings could endure the rigors 

of frequent fire. Most were filtered out, leaving oaks and yellow 

pines—and also probably chestnut, which unfortunately is 

absent from the age-structure graphs—to dominate the fire-prone 

mountainsides. The less fire-resistant species were relegated 

to parts of the landscape that were sheltered from fire. These 

sheltered locations would likely have included moist coves and 

ravines that housed diverse assemblages of mesophytic tree 

species. They also probably included rock outcrops and talus 

slopes where the sparseness and discontinuity of fine fuels 

inhibited fire and created refugia for such fire-sensitive tree 

species as Carolina hemlock (Tsuga caroliniana) and white pine 

(fig. 5.05). From such refugia, these fire-sensitive species could 

have expanded onto other sites after fires were excluded.

The unlogged watershed of Licklog Branch in the Great Smoky 

Mountains elucidates how fires filtered tree establishment and 

structured vegetation patterns across complex Appalachian terrain 

(Flatley and others 2015). As seen above (fig. 5.03), the chestnut 

oak stands at this site were dominated by an uneven-aged 

overstory of oaks that were recruited through the era of frequent 

burning. A pulse of oak establishment followed the last major 

fire in 1916, but it was the “other” species category that mostly 

benefitted from the altered fire regime (fig. 5.03).
83°50'0"W 83°49'30"W

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hemlock

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66 Chapter 5. Stand Age Structure and What it Indicates About Past Fire Regimes and Fire Effects on Vegetation

To place the dynamics of these oak stands into their broader 

landscape context, Flatley and others (2015) established plots 

along a topographic gradient spanning the entire southeastfacing slope from ridgetop to valley (fig. 5.06). The plots were 

situated in stands of yellow pine, chestnut oak, white pine–oak, 

and cove forest. The first three stand types covered most of the 

slope, and in these stands, xerophytic species prevailed among 

the trees that were established before fire exclusion (fig. 5.07, top 

panel). These xerophytes included pines, oaks, and a few other 

hardwoods. Xerophytic trees generally show greater resistance to 

fire than do mesophytic trees, apparently as an adaptation to dry 

sites where fires are common (Huston 1994), and therefore their 

prevalence on the slopes of Licklog Ridge was expected.

More surprising, however, was that xerophytic species composed 

about one-third of the pre-exclusion trees in the cove plots 

(fig. 5.07, top panel). These plots were located along Licklog 

Branch near the base of the slope (plots labeled “W” in fig. 5.06) 

in a mesic environment where xerophytic trees generally do not 

thrive because of competition with taller or more shade-tolerant 

Figure 5.06—Forest stands and sampling sites at the Licklog site that was studied by Flatley and others (2015). Plot locations are indicated by 

labeled squares, and fire-scarred trees are indicated by triangles. Locational data for plots, fire-scarred trees, and stands were obtained from Flatley 

and others (2015) and plotted on a topographic map obtained from the U.S. Geological Survey.

species (cf. Huston 1994). The presence of xerophytic species in 

the cove stands apparently reflects the occasional spread of fires 

from the southeast-facing slope down to the valley, where the 

fires maintained sufficiently open conditions for oaks and other 

xerophytic hardwoods to establish. Evidence of fire in the valley 

exists in the form of fire-scarred hemlocks and other trees along 

the edge of the stream (Flatley and others 2015).

A different picture emerges just across the branch, however, 

where the cove forest is sandwiched between the stream on its 

west and a northwest-facing slope to its east (plots labeled “E” 

in fig. 5.06). This “east cove” forest apparently was sheltered 

from frequent fire by the stream, which formed a barrier to fires 

spreading from the west, and by the steep northwest-facing 

slope, which was probably too moist to burn frequently down 

to the slope base. As a consequence, the sheltered east cove 

stands developed a contrasting composition in which nearly all 

the old, pre-exclusion trees are of mesophytic species (fig. 5.07, 

top panel).
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Fire History of the Appalachian Region: A Review and Synthesis 67

Figure 5.07—Percentage of tree establishment composed of xerophytic and 

mesophytic trees in each stand type by disturbance period at the Licklog site 

studied by Flatley and others (2015) across a topographic gradient. The frequentfire period includes the decades before the decade of the last fire (i.e., before the 

decade 1910–1919); the post-fire period includes the decades from 1910 to 1949 

in the immediate post-fire environment; and the mesophication period includes 

the decades after 1949, when stand closure and mesophication were occurring. 

This graph is based on data obtained from Flatley and others (2015) and 

resembles a figure in that publication. In general, the frequent-fire period favored 

the establishment of xerophytic species such as pine and oak across dry ridges, 

open slopes, and even moist cove sites that were exposed to fires spreading from 

the adjacent ridge. The establishment of mesophytic species was confined to 

sheltered sites near streams. Under the mesophication that has accompanied fire 

exclusion, mesophytic species have spread over the entire topographic gradient.
68 Chapter 5. Stand Age Structure and What it Indicates About Past Fire Regimes and Fire Effects on Vegetation

Tree establishment patterns changed across the entire southeastfacing slope of Licklog watershed under fire exclusion. 

Mesophytic species encroached into all the stands to dominate 

the young trees across the whole topographic gradient (fig. 5.07, 

middle and bottom panels). These changes support three 

important conclusions. First, frequent burning had filtered tree 

establishment in the past to favor oak and pine. This statement is 

supported by the fact that mesophytic species have found suitable 

habitat across the entire ridge in the absence of fire. Second, fire 

exclusion has favored the establishment of mesophytic species, as 

proposed in the mesophication hypothesis (Nowacki and Abrams 

2008). These mesophytic trees are poised to assume dominance 

of the stands as overstory pine and oak trees disappear, a 

successional replacement that is well underway in Licklog 

Branch and throughout much of the Appalachian region. Third, 

frequent burning helped shape the spatial patterns of vegetation 

across a landscape. At Licklog, it was not simply the well-known 

topographic moisture gradient that arranged tree species across a 

slope. It was, rather, the interaction of fire with this gradient that 

maintained the heterogeneous vegetation, with xerophytic pine 

and oak on the ridge and mesophytic species in moist, sheltered 

locations. Excluding fire has not merely altered the vegetation of 

individual stands. It has also changed the spatial arrangement of 

vegetation across a landscape.

CONCLUSIONS AND IMPLICATIONS

Data on tree age structure augment the fire-scar record by 

clarifying the severity of past fires as well as the influence of 

fires (and fire exclusion) on vegetation dynamics. Most fires 

recorded by fire-scarred trees were of low or moderate severity, 

and the fires would have maintained open stands dominated 

by pine, oak, and other fire-favored taxa. Fires appear to have 

flared occasionally into tree crowns in some of the Table 

Mountain pine–pitch pine stands that dominate south- or westfacing slopes at middle elevations. These crown fires killed a 

substantial portion of the overstory pines and made way for 

the establishment of new pine cohorts. These cohorts may also 

reflect other severe disturbances, such as ice storms and insect 

outbreaks. Severe disturbances may have been uncommon in 

low-elevation pine stands containing shortleaf or Virginia pines 

mixed with hardwoods. They were probably uncommon in oakdominated stands, as well.

The frequent passage of fires through pine- and oak-dominated 

stands played a filtering role in tree establishment and thereby 

controlled stand composition. Frequent burning created a 

rigorous environment that few tree seedlings could endure. Even 

the fire-adapted pines and oaks were recruited in fairly low 

numbers before fire exclusion. The occasional long fire interval 

was probably important for enabling oak sprouts to bolt to a fireresistant height before the next fire occurred. Less fire-resistant 

seedlings of red maple, hemlock, and other mesophytic tree 

species were largely prevented from establishing on the mountain 

slopes during the regime of frequent fire. These species were 

relegated to riparian areas and other sites that were sheltered from 

frequent fire. However, they rapidly encroached upslope onto the 

drier ridges once fires were excluded. As stands became more 

crowded, pine and oak recruitment diminished, with the result 

that stands currently dominated by old pine and oak trees harbor 

an understory containing mesophytic species. These mesophytic 

trees are poised to assume dominance as the overstory pines 

and oaks disappear over time. This ongoing mesophication is 

altering the topographic patterning of forest vegetation across 

entire landscapes.
Fire History of the Appalachian Region: A Review and Synthesis

69

Chapter 6. 

Appalachian Fire History as 

Reconstructed from Charcoal

generally angular shape, and by the way larger pieces fracture 

under pressure (Horn and Underwood 2014, Whitlock and Larsen 

2001). Wood charcoal is inert, recalcitrant, and can persist in 

soils for millennia (Fesenmyer and Christensen 2010, Hart 

and others 2008, Horn and Underwood 2014, Nelle and others 

2013). Its potential to resist decay is enhanced by higher burning 

temperatures (Scott 2010). Charcoal produced from non-woody 

plant parts, such as leaves and herbaceous stems, may be less 

resistant to decay in soils, based on its rarity in comparison to 

wood charcoal in soil charcoal samples; however, charcoal from 

non-woody plant tissues is preserved along with wood charcoal 

in lake and wetland sediments.

Analyses of charcoal in sediment cores to reconstruct fire history 

include studies of microscopic charcoal on slides prepared for 

pollen analysis (also called pollen-slide charcoal), and of larger, 

macroscopic charcoal fragments that are concentrated by sieving 

sediment samples (Whitlock and Larsen 2001) or examined on 

thin sections (Clark and Royall 1996). Whitlock and Larsen 

(2001) defined microscopic charcoal as particles < 0.0039 inch 

(100 μm or 0.1 mm) in size, although some larger particles may 

be present on pollen slides depending on the mesh size of the 

sieves used for pollen preparation (Horn and Underwood 2014). 

Studies of macroscopic charcoal in sediment cores make use 

of sieves with mesh sizes ≥ 0.0039 inch (100 μm), and often 

≥ 0.0049 inch (125 μm) or ≥ 0.0098 inch (250 μm). Studies 

of charcoal in soils focus almost exclusively on macroscopic 

charcoal, generally of still greater size—often ≥ 0.039 inch 

(1 mm) or ≥ 0.079 inch (2 mm) (Horn and Underwood 2014). 

Records of microscopic and macroscopic charcoal in sediment 

cores and soils provide evidence of fire activity at different spatial 

resolution. Microscopic charcoal particles are small enough to 

have been blown to a lake or wetland from outside the drainage 

basin (Clark and Patterson 1997, Hart and Buchanan 2012, Horn 

and Underwood 2014, Ohlson and Tryterud 2000, Scott 2010), 

and they may indicate regional fires. However, local fires may 

also deposit small charcoal in lakes and wetlands, or larger 

pieces may be broken up during transport and incorporation into 

sediments or during pollen sampling and processing. 

INTRODUCTION 

Although fire-scarred trees provide direct evidence of fire at local 

scales with annual or even seasonal resolution, the longest such 

records from the Appalachian region extend only about 400 years 

into the past. It would be useful to know about fire history under 

changing vegetation, climates, and land uses much deeper into 

the past. For example, was fire present throughout the roughly 

9,000 years that Native Americans inhabited the present-day 

Eastern United States before European contact?

Some information about the long-term history of fire can be 

obtained by analyzing charcoal fragments in soils and sediments 

(e.g., Ballard and others 2016, Clark 1988a, Fesenmyer and 

Christensen 2010, Hart and others 2008, Higuera and others 

2007, Horn and Underwood 2014, Patterson and others 1987, 

Whitlock and Larsen 2001). These charcoal fragments, which 

can be hundreds or thousands of years old, also provide direct 

evidence of fire occurrence, though not usually at the high 

temporal and spatial resolution of fire-scarred trees. The analysis 

of charcoal preserved in soils or in lake and wetland sediments 

can document how long fire has been present on a landscape 

or in a region. In cores of sediment extracted from lakes and 

wetlands, charcoal concentrations and accumulation rates often 

show temporal variations that suggest waxing and waning of 

fire activity over time. These inferred variations in fire activity 

can sometimes be linked to changes in vegetation, climate, 

or human land use documented by other materials preserved 

along with charcoal in sediment profiles, such as pollen grains, 

diatoms, and stable isotope signatures, or documented by other 

paleoenvironmental or archaeological research. 

Charcoal forms from the incomplete combustion of organic 

material, generally plants, by fire at temperatures > 518 oF 

(> 270 °C) (Orvis and others 2005, Scott 2010). Fires produce 

charcoal fragments of various sizes that are incorporated into 

soils of the burn site, or are washed or blown away, sometimes 

to lakes or wetlands, where fragments may be preserved in 

accumulating sediments. Researchers distinguish charcoal 

fragments from other dark organic particles in soils and 

sediments by their black sheen under reflected light, by their 
70 Chapter 6. Appalachian Fire History as Reconstructed from Charcoal

In contrast to microscopic charcoal, which may reflect fires both 

near and distant from the depositional site, macroscopic charcoal 

particles in sediments and soils provide evidence of local fires. 

In lake and wetland sediments, they usually indicate fires within 

the watershed or close by, with charcoal transported relatively 

short distances by wind and water (Clark and Patterson 1997, 

Higuera and others 2007, Whitlock and Larsen 2001). In soils, 

the large macroscopic charcoal fragments that researchers study 

are interpreted to reflect charcoal left in place following fires at 

the sampling site or moved only tens of feet by gravity or water 

(Gavin and others 2003, Ohlson and Tryterud 2000).

The nature and amount of charcoal produced by a fire depends 

on many factors, such as its size and intensity, and the type of 

fuel it burns. For example, crown-fire regimes often produce 

wood particles from the charred trees, whereas fire regimes with 

frequent and efficient burning of fine surface fuels may produce 

relatively little charcoal (Whitlock and Larsen 2001). Charcoal 

accumulation depends on terrain, vegetation, and other landscape 

features. A large watershed with steep slopes draining into a 

small lake, for example, will amplify charcoal accumulation in 

the lake sediments compared to a smaller, less-steep watershed 

draining into a large lake (Whitlock and Larsen 2001). A fringe of 

riparian vegetation will trap some of the charcoal and prevent its 

deposition in the lake.

SEDIMENT CHARCOAL ANALYSIS

To sample the amount of charcoal in lake or wetland sediments, 

researchers collect cores of sediment using piston corers operated 

on lakes from anchored floating platforms made from inflatable 

rafts, canoes, or inner tubes (fig. 6.01). Cores are generally 

collected in successive 3.28-feet (1-m) sections (fig. 6.02) from 

positions near the centers of lakes. Each core provides a history 

of charcoal deposition, with younger sediment and charcoal at 

the top of the core and older material at the bottom. After the 

cores are transported to the laboratory, core sections are sliced 

lengthwise and sediment samples are removed from the cut faces 

for analysis. 

In microscopic charcoal analysis, samples of 0.015–0.061 cubic 

inch (0.25–1.0 cm3) are removed at intervals along the core 

(often ≥ 3.15 inches, or 8 cm) and placed in small test tubes 

for chemical processing to dissolve and remove minerals and 

extraneous organic matter. The resulting “pollen residues” 

are mounted on microscope slides and examined at 400× 

magnification using compound microscopes to reconstruct 

vegetation history (from pollen) together with fire history from 

microscopic charcoal. Charcoal abundance is determined by 

counting particles or estimating charcoal particle area; in some 

Figure 6.01—Collecting sediment from the bottom of Crystal Lake in eastern 

Tennessee by using a raft as a platform from which to operate the corer. Here 

researchers are recovering a mud-water interface core that is offset from the rest 

of the core sections, which are collected from the hole in the center of the raft. 

Figure 6.02—Extruding a sediment core section from a piston corer. 
Fire History of the Appalachian Region: A Review and Synthesis 71

studies, graminoid charcoal produced by grasses or sedges is 

counted separately (Robinson and others 2005). Various charcoal 

indices are reported in studies of microscopic charcoal, including 

concentration (charcoal fragments or area by volume or mass, 

e.g., particles per cubic inch, or particles cm-3); influx (charcoal 

fragments or area by core site area by year, e.g., square inches 

of charcoal per square inch per year, or mm2 charcoal cm-2 yr-1); 

or charcoal-to-pollen ratios (fragment counts or area per pollen 

grain in the samples (Ballard and others 2016). 

Because pollen is sampled at intervals in sediment cores, 

microscopic charcoal records developed from pollen slides will 

not capture all fire events that may be recorded in the lake or 

wetland sediments: gaps between samples can include missed 

fire events. This sampling method, together with the uncertain 

source area for the microscopic charcoal particles (Whitlock and 

Larsen 2001), results in records of fire that are temporally and 

spatially coarse. However, the ability to directly tie the evidence 

for fire with pollen evidence for shifts in vegetation from the 

same slides makes microscopic charcoal records valuable for 

understanding relationships between fire and vegetation over long 

time periods (Ballard and others 2016). Also, the sediments at 

some core sites may contain insufficient macroscopic charcoal 

for analysis, but ample microscopic charcoal. The presence of 

relatively high amounts of microscopic charcoal but low amounts 

of macroscopic charcoal may reflect processes of charcoal 

production and transport within watersheds and depositional 

basins as well as local fire history. 

Macroscopic charcoal analysis differs from microscopic charcoal 

analysis in that samples are taken at close or continuous intervals, 

minimizing or eliminating the chance of missed fire events, and 

are processed without extensive chemical treatment. We focus 

here on macroscopic charcoal analysis based on sieving; see 

Clark (1988b) for the thin section technique. Although some 

researchers sieve sediment samples with a volume of 0.061 

cubic inch (1 cm3), larger sample volumes of 0.122–0.244 cubic 

inch (2–4 cm3) may be necessary to achieve replicable counts in 

some settings (Carcaillet and others 2001, Schlachter and Horn 

2010). The highest resolution fire history records developed from 

unlaminated sediment cores are based on sampling charcoal at 

continuous 0.394-inch (1-cm) intervals, with samples cut from 

core section faces using knives or rectangular samplers that allow 

removal of contiguous samples (Schlachter and Horn 2010). 

Some researchers have sampled sediment cores at finer intervals, 

but doing so may not improve the resolution of the charcoal 

record owing to blurring of the record by bioturbation (Whitlock 

and Larsen 2001).

Samples are first disaggregated by using hot distilled water or 

chemical solutions [often sodium hexametaphosphate, potassium 

or sodium hydroxide, hydrogen peroxide, or sodium hypochlorite 

(bleach)] and then sieved to concentrate charcoal of a particular 

size class or classes. Mesh sizes commonly used for sieving 

macroscopic charcoal samples include 0.005, 0.007, 0.010, and 

0.020 inch (125, 180, 250, and 500 μm) (League and Horn 2000, 

Lynch and Clark 2002, Whitlock and Larsen 2001). Charcoal is 

examined wet on sieves, or after transferring to Petri dishes (wet 

or dry), to determine particle counts and in some cases particle 

area “by eye” using a dissecting scope or using image analysis. 

Researchers studying macroscopic charcoal in a sediment core 

might also investigate pollen evidence of vegetation change, 

but this requires separate processing of samples for microscopic 

analysis. Macroscopic charcoal abundance in sediment cores is 

typically presented as charcoal concentration (charcoal particle 

numbers, area, or mass by volume or mass) or as influx (charcoal 

particle numbers, area, or mass per square inch per year, or cm2

per year), which is also referred to as charcoal accumulation rate, 

or CHAR, in some studies (Whitlock and Larsen 2001). 

To develop a chronology for the sediment core, the researcher 

collects charcoal or other organic fragments from different levels 

in the core and sends them to a laboratory for radiocarbon dating 

using accelerator mass spectrometry (AMS), which can provide 

dates for organic materials up to approximately 45,000 years 

old (Horn and Underwood 2014). In addition, lead-210 dating is 

often used to provide higher-resolution dating for lake sediments 

deposited during approximately the last 200 years (Appleby 

2008, Whitlock and Larsen 2001). 

Computer software programs (e.g., CALIB; Stuiver and Reimer 

1993) linked to calibration datasets (Reimer and others 2013) 

allow researchers to convert the radiocarbon age of each dated 

sample to calendar years before “present” (defined as the year 

1950), usually expressed as “cal yr BP.” The calibrated age is 

presented as a range such that there is a 95-percent probability 

that the true age of the sample falls somewhere in this range. The 

radiocarbon age represents the time since carbon was removed 

from the atmosphere and incorporated in the wood, and not the 

age of the fire that produced the charcoal (Gavin 2001, Gavin and 

others 2003, Sanford and others 1985). This “inbuilt” age of the 

charcoal must also be taken into account in estimating the timing 

of past fires. Fesenmyer and Christensen (2010) estimated the 

inbuilt age of charcoal in the southern Appalachian region to be 

on the order of 50–100 years. This inbuilt age must be added to 

the calibrated age range of a sample. For example, a sample with 
72 Chapter 6. Appalachian Fire History as Reconstructed from Charcoal

a calibrated age of 650–480 cal yr BP has an estimated age of 

650–380 cal yr BP when the inbuilt age is added to the age range 

(Horn and Underwood 2014).

In cores of sediment from lakes and wetlands, radiocarbon 

dates on charcoal or other organic particles provide ages for the 

levels in the core from which they were obtained. The ages for 

intervening levels of the core can be estimated through linear 

interpolation or other methods of age modeling. Sufficient 

radiocarbon dates must be obtained for sediment cores to allow 

researchers to recognize dates that are outliers representing the 

intrusion or incorporation of material younger or older than 

surrounding material; these dates should not be used in the 

development of chronologies. Because charcoal can persist for 

long periods on the landscape and in soils, charcoal is more likely 

than unburned organic material to yield dates that are older than 

expected at a particular depth in a core. In these cases, the age 

of the charcoal predates the age of surrounding core material 

and should be excluded from the age model. However, old 

charcoal pieces that are outliers in age models still contribute to 

understanding fire history by documenting the timing of earlier 

fires. Their occurrence in sediment profiles may have additional 

paleoenvironmental significance, potentially signaling major 

erosive events in watersheds (Kennedy and others 2006). 

Despite the constraints imposed by uncertainty in calibrated ages 

and age models, and the possibility of unrecognized outliers, 

researchers studying charcoal in sediment cores have been able 

to interpret temporal variations in charcoal accumulation to 

understand how fire regimes have changed over time within 

watersheds and regions. For some macroscopic charcoal 

records of watershed fires, researchers have estimated mean 

fire interval (MFI). These estimates require the researcher to 

decompose the charcoal time series into two components, a 

low-frequency “background component” and a high-frequency 

“peaks component” (Whitlock and Larsen 2001). The background 

charcoal deposition can represent multiple sources, including 

“secondary” charcoal that is stored in the watershed and delivered 

to the lake for years or even decades following a fire, and possible 

fallout from regional fires outside the watershed, although 

macroscopic charcoal is generally interpreted to reflect fires 

within watersheds or nearby, rather than regional fires. Observed 

trends in background charcoal have also been interpreted to 

result from long-term changes in vegetation that alter fuel loads 

in watersheds (Millspaugh and others 2000). Charcoal peaks, 

on the other hand, represent the charcoal from a fire event in the 

watershed. A fire event is not necessarily a single fire, however, 

because it could result from multiple fires within the period 

spanned by the charcoal peak. Therefore, the peak may represent 

an episode of frequent burning. Using charcoal peaks to estimate 

MFI indicates the frequency of fire events and not necessarily of 

individual fires.

Whether a charcoal time series is suitable for estimating MFI 

depends on the temporal resolution of the charcoal record 

compared to the MFI. The resolution of a charcoal record reflects 

the sedimentation rate in the lake or wetland and the spacing of 

samples in the core. Rapid sedimentation permits high-resolution 

reconstructions because each centimeter of the core represents 

sediment deposited over only a few years. For lakes in temperate 

North America, Whitlock and Larsen (2001) suggested that 

0.394 inch (1 cm) of sediment typically represents 5–20 years 

of deposition (e.g., sedimentation rates of 0.020–0.079 inch per 

year, or 0.05–0.2 cm yr-1). Thus, it is not possible to resolve 

whether the charcoal in that 1-cm segment of core originated 

from one fire or from several.

Studies of charcoal in sediment cores from lakes and wetlands 

in the Appalachian region have revealed sedimentation rates of 

< 0.001 inch per year to 0.142 inch per year, or 0.002–0.36 cm 

yr-1 (Lynch and Clark 2002), i.e., significantly lower for some 

time periods at some sites than for the typical eastern lakes in 

the example above. The intervals of very low apparent sediment 

accumulation may reflect intervals of missing sediment, perhaps 

associated with droughts. The consequence for reconstructing 

past fires is that 0.394 inch (1 cm) of sediment that accumulated 

at the slow end of the range shown by Appalachian lakes would 

represent as many as 500 years, resulting in a fire record of 

very low temporal resolution, even if sampled at contiguous 

0.394- inch (1-cm) intervals. Even at sites with the highest 

sedimentation rates, where 0.394 inch (1 cm) of sediment 

could represent less than 3 years for some core sections, it will 

be impossible to distinguish individual fires if they recurred 

at intervals of only a few years, as we have found in firescar analyses at our sites in the Appalachians (see chapter 3). 

Whitlock and Larsen (2001) recommended that to estimate MFI 

from a sediment charcoal series, sample resolution should be 

approximately one-eighth the MFI (Whitlock and Larsen 2001), 

meaning that a 5-year resolution would permit MFI estimates 
Fire History of the Appalachian Region: A Review and Synthesis 73

Figure 6.03—Using a single root auger to collect soil charcoal.

for a fire regime with MFI ≥ 40 years. Thus, sediment charcoal 

analysis in the Appalachian region is ill suited for reconstructing 

MFI estimates for past intervals in which fire regimes were 

characterized by the high fire frequencies we have reconstructed 

for recent centuries. However, charcoal analysis is nevertheless 

valuable in providing evidence of watershed and regional 

fires prior to the last few hundred years, and of changes over 

time in relative fire activity resulting from changes in human 

activity, climate, and vegetation going back as far as the late 

glacial period. 

Although charcoal records from most lakes in the Appalachian 

region or worldwide cannot provide the annual resolution of 

tree-ring-based fire records, a rare type of lake sediment offers 

the possibility of annually resolved charcoal records. Varved 

lake sediments with annual laminations are found in some lakes 

with anoxic deepwater (Zolitschka 2007), including two at the 

northern edge of the Appalachian region, where Clark and Royall 

(1996) reconstructed high-resolution fire histories by using thinsection analyses of varved sediments.

SOIL CHARCOAL ANALYSIS

Following fires, some charcoal stays within the burn area, where 

it is incorporated into the soil profile and provides site-specific 

evidence of past fires. In the Appalachian region, where few 

lakes or wetlands exist, this soil charcoal may be the best source 

of long-term fire history data. Horn and Underwood (2014) 

recommended a procedure for soil charcoal collection and 

analysis, and here we summarize their procedure.

Although charcoal can be recovered from the walls of excavated 

soil pits, most researchers collect samples by using a soil corer 

(fig. 6.03), which saves time, reduces environmental impact, 

and can be accomplished in the rain. A popular coring device for 

collecting samples for soil charcoal analysis is the “single root 

auger” manufactured by Eijkelkamp, which despite its name has 

a cylindrical, rather than helical, cutting head (Horn and others 

1994, Horn and Underwood 2014). These augers collect soil 

cores of 3.15 inches (8 cm) in diameter and up to 39.37 inches 

(100 cm) in length, in increments of 1.97 or 3.94 inches (5 or 

10 cm). A pressure plate in the device facilitates extrusion of 

each core increment into a labeled plastic bag for return to the 

laboratory (figs. 6.04, 6.05). 
74 Chapter 6. Appalachian Fire History as Reconstructed from Charcoal

Figure 6.04—Extrusion of a 3.94-inch (10-cm) soil core into a labeled plastic bag.

Figure 6.05—Close-up view of a soil core in which charcoal fragments are visible.
Fire History of the Appalachian Region: A Review and Synthesis 75

Figure 6.06—Macroscopic charcoal from study sites in Great 

Smoky Mountains National Park. The upper photograph 

shows charcoal from red maple (Acer rubrum L.). Anatomical 

features that allow identification of red maple are narrow rays 

that are approximately the same width as the widest pores, 

absence of tyloses, and diffuse-porous wood. The lower 

photograph shows charcoal from a southern yellow pine 

(Pinus, diploxylon group). Anatomical features that allow 

identification of southern yellow pine are tracheids, resin 

canals, and pronounced earlywood to latewood transition at 

ring boundaries. The wood anatomy of the diploxylon pines 

that grow in the southern Appalachian Mountains is too similar 

to allow differentiation of charcoal specimens to species. The 

scale bar is approximate and is for both photographs. (photos 

by Christopher A. Underwood)

In the laboratory, researchers separate charcoal fragments 

from the soil by first soaking the samples in water overnight. 

Following disaggregation by water, samples are wet-sieved using 

an 8-inch diameter sieve with a 0.079-inch (2-mm) mesh. The 

material retained on the sieve is examined, either on the sieve or 

after transfer to a large plate or dish, under a dissecting scope. 

Charcoal fragments are picked using forceps and washed with 

distilled water. From there, charcoal fragments are placed in glass 

vials and dried in a laboratory oven at 194 °F (90 °C). 

After the charcoal fragments are dried, researchers weigh 

the fragments to determine the charcoal mass in the soil core 

increment (usually reported as ounces of charcoal per cubic inch, 

or g charcoal cm-3) and then select fragments for taxonomic 

identification and radiocarbon dating. In soils of the Appalachian 

region, the depth at which charcoal fragments are found is 

generally not a reliable indicator of their relative age, i.e., deeper 

fragments are not necessarily older (Fesenmyer and Christensen 

2010), because physical and biological factors mix the soil. 

Hence, random selection of individual fragments for dating 

may have advantages over selecting samples based on depth in 

the soil core (Hammond and others 2007), as would be done 

in the analysis of a lake sediment core. Following radiocarbon 

determination, radiocarbon dates are converted to calendar-year 

ages, as described above for sediment charcoal, taking into 

account possible inbuilt age. Taxonomic identification must be 

done prior to radiocarbon dating because samples are destroyed 

in the dating process. Charcoal fragments can be identified to 

species (e.g., Acer rubrum) or subgenus (e.g., Pinus, diploxylon 

group) based on distinctive wood anatomy (fig. 6.06); this 

identification provides key information on the plants present at 

the burn site at the time of the fire.

The lack of a depth-age relationship for charcoal in soils 

is disadvantageous for reconstructing fire history from soil 

charcoal. Unlike studies of charcoal in sediment cores, for 

which a chronology can be developed based on a relatively 

small number of radiocarbon dates and used to infer the ages of 

charcoal particles in samples between dated horizons, the age of 

a soil charcoal fragment cannot be estimated from radiocarbon 

dates that bracket it in the soil profile. Therefore, researchers 

must date numerous pieces of charcoal to obtain a record of fire 

activity. This is an expensive undertaking, given the standard cost 

for AMS radiocarbon dates of about $500–600 per date.

Soil charcoal offers some compensating advantages, however. 

The first is that evidence is site specific. Soil charcoal indicates 

that a fire occurred at or very near the location where the charcoal 

was found. In contrast, charcoal in lake or wetland sediments 

reflects fires within the drainage basin, at best, and possibly 

from the broader region. A second advantage of soil charcoal is 

the ability to identify the tree or shrub taxon from the charcoal, 

providing information about vegetation history at a specific site 

with collocated fire history information. Finally, the method 

is applicable over wide areas, facilitating the collection of fire 

history information from the specific site of interest. Soil charcoal 

analysis is not restricted to the rare natural lakes and wetlands 

of the Appalachian region or to forest stands with trees that scar 

in fires.
76 Chapter 6. Appalachian Fire History as Reconstructed from Charcoal

CHARCOAL-BASED FIRE HISTORY RESEARCH 

IN THE APPALACHIAN REGION

Here we present, and seek to compare and synthesize, charcoalbased reconstructions of past fire at selected study sites across 

the Appalachian region (fig. 6.07). To do this, we have prepared 

a series of charcoal graphs using a standard graph format that 

facilitates comparison. We must state at the outset, however, 

that comparison is complicated by a number of factors. The sites 

we include in our review were sampled by several researchers 

using different techniques. One major difference is whether the 

researchers studied charcoal in sediment or soil, but there are also 

variations in the manner of collecting and analyzing the charcoal. 

Additionally, the lake and wetland sites investigated for sediment 

charcoal analyses differ in size, type (lake or pond versus bog), 

and topographic situation. However, despite the constraints, 

our review of selected records provides a long-term perspective 

without which the shorter records of fire from scarred trees and 

other sources would be unmoored from their historical context.

We used charcoal values provided in tables or that we estimated 

from diagrams in the original studies to generate graphs 

depicting changes over time in charcoal accumulation or relative 

abundance. Although the graph format was standardized, the 

y-axis scales are based on the range of charcoal values in the 

study and so they differ between graphs. Some difference also 

exists in the charcoal measures, or indices, plotted, as these also 

differ between the original studies. We added shading to show 

the Archaic (9,500–2,800 BP), Woodland (2,800–1,000 BP), 

and Mississippian (1,000–300 BP) Archaeological Periods and 

the Historic Period (300 BP to present), based on Delcourt and 

others (1986). Where available, we also added pollen data from 

the sites. 

We present the graphs in four groups according to their temporal 

resolution and charcoal source (sediment or soil): 

(1) High-resolution sediment charcoal records with annual to 

decadal resolution. We used the graphs in each study to estimate 

the charcoal value for each decade and then plotted the decadeto-decade variations on our graphs. 

(2) Sediment charcoal records from sites with moderate to high 

sedimentation rates that appear to resolve the general trend in 

fire activity at each site across the past millennium. For each 

of these sites, we have summarized charcoal level by century, 

so the graphs furnish a view of century-to-century variation in 

charcoal accumulation. 

(3) Long sediment charcoal records that show variations over 

many millennia. We have summarized these data for 500-year 

intervals to portray the broad changes and to accommodate 

charcoal records that have modest resolution because of low 

sedimentation rate or sampling procedure (i.e., sampling at 

intervals along a core instead of continuously at 1-cm intervals). 

(4) Soil charcoal records summarized at a 500-year resolution and 

yielding multimillennial records.

High-Resolution Charcoal Records

Three sites in the Appalachian region have yielded highresolution records of fire covering 1,000 to > 8,000 years 

(figs. 6.08–6.10). The charcoal record from Trout Pond 

(fig. 6.08A) is the record of highest temporal resolution in a 

series of sediment charcoal records developed by Lynch and 

Clark (2002) using macroscopic charcoal (≥ 0.0071 inch, or 

180 μm) from sites in the Blue Ridge Mountains and the Ridge 

and Valley province in North Carolina, Virginia, West Virginia, 

and Maryland. Trout Pond is a small natural lake that fills a 

sinkhole formed by dissolution of limestone bedrock in the Ridge 

and Valley province of eastern West Virginia.3 The pond is fed 

by streams draining the slopes of a nearby mountain. The fire 

history record developed from the sediments of this lake, and 

supported by three radiocarbon dates together with lead-210 

analyses, extends back nearly a millennium. The record shows 

fairly consistent background charcoal deposition (about 0.05–

0.02 square inch per square inch per year, or 0.5–2.0 mm2 cm–2

yr–1), which may indicate frequent surface fires, superimposed 

by charcoal peaks of varying magnitude. These peaks could 

represent crown or mixed-severity fires that affected parts of the 

drainage basin. The Trout Pond charcoal record seems consistent 

with tree-ring studies, which indicate a regime of frequent, 

low-severity fires that, at least in pine stands, were punctuated 

occasionally by mixed- or high-severity fires that facilitated tree 

establishment (chapters 4 and 5). These consistencies suggest that 

the fire regime of the last few centuries (as indicated by fire scars) 

is similar to that which prevailed over the whole millennium.

The Ely Lake (fig. 6.08B) and Devil’s Bathtub (fig. 6.08C) 

sites in Pennsylvania and New York yielded longer records of 

burning that extend back about 2,300 years and 10,500 years, 

respectively. These lakes were sampled as part of a study 

comprising seven sites across the Northeastern United States and 

Great Lakes (Clark and others 1996, Clark and Royall 1996), 

but these two are the only sites that fall within the Appalachian 

Mountains. At both lakes, sediments are characterized by varves 

3 Personal communication. April 27, 2016. Steven Q. Croy, Ecologist/Fire 

Planner, George Washington and Jefferson National Forests, U.S. Forest Service. 

5162 Valleypointe Parkway, Roanoke, VA 24019.
Charcoal study categories 

Sediment

Soil

Figure 6.07—Locations of sediment and soil charcoal sites examined in this report. Site labels indicate the 

authors of the studies and the site names. C&R = Clark and Royall (1996), Delcourt and others = Delcourt 

and others (1998), D&D = Delcourt and Delcourt (1998), F&C = Fesenmyer and Christensen (2010), Hart 

and others = Hart and others (2008), L&C = Lynch and Clark (2002), Underwood = Underwood (2013).

Fire History of the Appalachian Region: A Review and Synthesis 77
0.35

0.30

0.25

0.20

0.15

0.10

0.05

0.00

0.35

0.30

0.25

0.20

0.15

0.10

0.05

0.00

Lynch and Clark (2002)

Trout Pond, WV Sediment Charcoal MISS HIST

1000 800 600 400 200 0

Calibrated years BP

Charcoal accumulation

(in 2 in -2 yr -1)

MISS

0.35

0.30

0.25

0.20

0.15

0.10

0.05

0.00

0.35

0.30

0.25

0.20

0.15

0.10

0.05

0.00

Clark and Royall (1996)

Ely Lake, PA Sediment Charcoal WOOD HIST

2200 2000 1800 1600 1400 1200 1000 800 600 400 200 0

Calibrated years BP

Charcoal accumulation

(in 2 in -2 yr -1) 2.25

2.00

1.75

1.50

1.25

1.00

0.75

0.50

0.25

0.00

2.25

2.00

1.75

1.50

1.25

1.00

0.75

0.50

0.25

0.00

Clark and others (1996)

Devil’s Bathtub, NY MISS HIST

12000 10000 8000 6000 4000 2000 0

Calibrated years BP

Charcoal accumulation

(in 2 in -2 yr -1)

ARCH WOOD Sediment 

Charcoal

(A)

(B)

(C)

78 Chapter 6. Appalachian Fire History as Reconstructed from Charcoal

Figure 6.08—High-resolution (decadal) estimates of charcoal levels for (A) Trout Pond, (B) Ely Lake, 

and (C) Devil’s Bathtub. Background shading indicates the Archaic (ARCH; 9,500–2,800 BP), Woodland 

(WOOD; 2,800–1,000 BP), and Mississippian (MISS; 1,000–300 BP) archaeological periods and the Historic 

Period (HIST; 300 BP–present). Fairly consistent deposition of charcoal particles at Trout Pond and Ely Lake 

throughout the record suggests frequent surface fires. At Devil’s Bathtub, the transition from high rates of 

charcoal deposition to lower rates of deposition was related to a shift from jack pine to white pine and probably 

a concurrent trend from crown fires to surface fires.
Fire History of the Appalachian Region: A Review and Synthesis 79

or annual laminations, which in combination with radiocarbon 

dating and the identification of cultural horizons in pollen data 

provided high-resolution chronologies for the charcoal records. 

The near-surface sediments of Devil’s Bathtub were not varved, 

however, so the researchers did not analyze the last 2,300 years 

of charcoal deposition at this site. For both sites, charcoal was 

examined on thin sections prepared from the lake sediments, a 

method that makes it possible to count charcoal particles in varve 

couplets corresponding to single years. The researchers counted 

charcoal fragments ≥ 0.0024 inch, or 60 μm, in size.

Ely Lake is located within a hardwood–hemlock forest on 

a rolling section of the Appalachian Plateau. It had a low 

sedimentation rate, and charcoal accumulation suggested a 

relatively consistent level of fire activity over the entire record. 

Clark and Royall (1996) had expected to see a rise in charcoal 

accumulation associated with the inception of maize agriculture 

among the Iroquois during the past millennium, but no such 

change is evident, a finding interpreted by Clark and Royall to 

mean that Iroquois burning was probably confined to the vicinity 

of settlements and did not affect more remote locations around 

Ely Lake.

Devil’s Bathtub is on the till plain about 12 miles north of the 

Appalachian Plateau in an area primarily covered with northern 

hardwoods forest under the current climate but with other 

hardwoods and conifers also present. For this site, Clark and 

others (1996) also analyzed pollen to reconstruct vegetation 

changes; they found that fire history corresponded with vegetation 

changes over the Holocene. Early in the record, when jack pine 

was an important constituent of the forest, crown fires were more 

common, as indicated by large charcoal peaks. The diminution of 

these peaks about 8,000–9,000 years ago may indicate a change 

from crown fires to surface fires with the transition to white pine. 

Later, fire frequency declined with the expansion of hardwoods 

about 8,000 years ago.

Century-to-Century Charcoal Variations 

Over the Past Millennium

In this subsection, we explore patterns of fire activity over the 

last millennium in the records of multiple sites with charcoal time 

series of moderate to high resolution, summarized at intervals of 

one century for this common period. The past 1,000 years spans 

the Mississippian Archaeological Period (1,000–300 BP) and the 

Historic Period (300 BP–present). 

The six sites for which we present charcoal diagrams (fig. 6.09) 

are located mainly within the southern Blue Ridge Mountains 

and the Ridge and Valley province, with one site on the Piedmont 

and one on the Appalachian Plateau. This plateau site (Ely Lake) 

and one Ridge and Valley site (Trout Pond) were discussed in the 

previous subsection, but here we have aggregated the charcoal 

records to the century scale to compare with the remaining, 

lower-resolution records. 

At two sites (Trout Pond and Ely Lake; fig. 6.09A and B), fire 

appears to have been present over the last millennium but to 

have varied from century to century, especially at Trout Pond. 

The relatively low values for the most recent century probably 

correspond to fire exclusion. At White Oak Bog in the southern 

Blue Ridge Mountains (fig. 6.09C), fire activity increased during 

the late Mississippian Period, possibly reflecting agricultural 

intensification and/or expanding human population. Fire activity 

peaked during the Historic Period.

The records for the three remaining sites are distinct in some 

respects from all others. The Days Creek record (fig. 6.09D) 

exhibits high charcoal accumulation in the most recent century, a 

pattern that may reflect heavy soil erosion and hence accelerated 

charcoal delivery from this Piedmont landscape. Charcoal 

accumulation during the prehistoric period is consistent with a 

rise in fire activity during the middle to late Mississippian Period. 

The Mountain Lake record (fig. 6.09E) from a high-elevation 

site in the Ridge and Valley province shows little or no charcoal 

accumulation until European settlement, likely a consequence 

of the remoteness of the site and the incombustible nature of 

the northern hardwoods–hemlock forest on the surrounding 

landscape. A most unusual pattern is evident at Pink Beds Bog 

(fig. 6.09F) in the southern Blue Ridge Mountains, where fire 

activity apparently declined in the middle Mississippian Period 

and then remained low.

On the basis of these six study sites, it seems reasonable to 

conclude that fire activity was relatively high during the middle 

and late Mississippian Period, and in general that it remained 

high during the Historic Period. Nonetheless, the dating of these 

charcoal records is somewhat imprecise, as is the translation 

between charcoal accumulation and fire activity. Additionally, 

the data for five of the six study sites come from an unpublished 

study (Lynch and Clark 2002). Although we chose the records in 

which we had more confidence to include in this discussion, all 

of them have low numbers of radiocarbon dates and some were 

characterized by slow sedimentation. One site, Mountain Lake, 

has a dynamic geomorphic setting characterized by periodic 

disruption of sedimentation (e.g., Cawley and others 2001).

Given these limitations, we attempted to distill the most 

basic patterns across the six sites by using a ranking method. 

Specifically, for each study site we ranked the 10 centuries of the 

millennium by charcoal accumulation, assigning a rank of 10 to 

the century with the highest value and a rank of 1 to the century 

with the lowest value. For centuries with tied values (including 

zeroes), we assigned the average rank for all the centuries 

with tied values. We then averaged the ranks for each century 

across all six sites (fig. 6.10). Thus synthesized, the charcoal 

records suggest a moderate to high level of burning through the 

Mississippian Period, with slightly higher ranks between 900 and 

400 cal yr BP than for the rest of the period. They also indicate 

that frequent burning continued into the early Historic Period and 

peaked during the 19th century.
0.08

0.07

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0.01

0.00

0.08

0.07

0.06

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0.03

0.02

0.01

0.00

Lynch and Clark (2002)

Trout Pond, WV

1000 800 600 400 200 0

Calibrated years BP

Sediment Charcoal MISS HIST

Charcoal accumulation

(in 2 in -2 yr -1)

0.06

0.05

0.04

0.03

0.02

0.01

0.00

0.06

0.05

0.04

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0.01

0.00

Clark and Royall (1996)

Ely Lake, PA

1000 800 600 400 200 0

Calibrated years BP

Sediment Charcoal MISS HIST

Charcoal accumulation

(in 2 in -2 yr -1) 0.0040

0.0035

0.0030

0.0025

0.0020

0.0015

0.0010

0.0005

0.0000

0.0040

0.0035

0.0030

0.0025

0.0020

0.0015

0.0010

0.0005

0.0000

Lynch and Clark (2002)

White Oak Bog, NC

1000 800 600 400 200 0

Calibrated years BP

Sediment Charcoal MISS HIST

Charcoal accumulation

(in 2 in -2 yr -1)

(A)

(B)

(C)

80 Chapter 6. Appalachian Fire History as Reconstructed from Charcoal

Figure 6.09—Estimates of charcoal level for each century over the past millennium for (A) Trout Pond, (B) Ely Lake, 

(C) White Oak Bog, (D) Days Creek, (E) Mountain Lake, and (F) Pink Beds Bog. Background shading as in figure 

6.08. MISS = Mississippian Period, HIST = Historic Period. The charcoal levels indicate century-scale variations in 

fire activity and suggest that fire was relatively common at most sites during the MISS and HIST periods. 

(continued on next page)
Lynch and Clark (2002)

Days Creek, VA

1000 800 600 400 200 0

Calibrated years BP

Sediment Charcoal MISS HIST

Charcoal accumulation

(in 2 in -2 yr -1) 0.00200

0.00175

0.00150

0.00125

0.00100

0.00075

0.00050

0.00025

0.00000

0.00200

0.00175

0.00150

0.00125

0.00100

0.00075

0.00050

0.00025

0.00000

Lynch and Clark (2002)

Mountain Lake, VA

1000 800 600 400 200 0

Calibrated years BP

Sediment Charcoal MISS HIST

Charcoal accumulation

(in 2 in -2 yr -1) 0.0030

0.0025

0.0020

0.0015

0.0010

0.0005

0.0000

0.0030

0.0025

0.0020

0.0015

0.0010

0.0005

0.0000

Lynch and Clark (2002)

Pink Beds Bog, NC

1000 800 600 400 200 0

Calibrated years BP

Sediment Charcoal MISS HIST

Charcoal accumulation

(in 2 in -2 yr -1)

0.0015

0.0012

0.0009

0.0006

0.0003

0.0000

0.0015

0.0012

0.0009

0.0006

0.0003

0.0000

(D)

(E)

(F)

Fire History of the Appalachian Region: A Review and Synthesis 81

Figure 6.09 (continued)—Estimates of charcoal level for each century over the past millennium for (D) Days Creek, 

(E) Mountain Lake, and (F) Pink Beds Bog. Background shading as in figure 6.08. MISS = Mississippian Period, 

HIST = Historic Period. The charcoal levels indicate century-scale variations in fire activity and suggest that fire was 

relatively common at most sites during the MISS and HIST periods. 
Average charcoal accumulation 

rank by century

1000 800 600 400 200 0

Calibrated years BP

Sediment Charcoal MISS HIST

Average rank

10

8

6

4

2

0

10

8

6

4

2

0

82 Chapter 6. Appalachian Fire History as Reconstructed from Charcoal

Figure 6.10—Average rank of charcoal level for each century of the past millennium among the six 

study sites portrayed in figure 6.09. Centuries with higher mean ranks (maximum possible rank = 10) are 

represented, on average, by higher levels of charcoal at the six study sites than are centuries with lower 

mean ranks (minimum possible rank = 1). MISS = Mississippian Period, HIST = Historic Period.

A Multimillennial View of Fire History at Coarse 

Resolution from Sediment Charcoal

To place the most recent millennium of fire history into the 

broadest possible temporal context, we now enlarge our 

perspective by using longer (multimillennial) records from seven 

sediment charcoal sites distributed across the Appalachian region 

(fig. 6.11). Low sedimentation rates limit the resolution of some 

of these records, so we have aggregated the data to 500-year 

intervals. For several of the sites, pollen data were presented 

in addition to charcoal, allowing us to summarize pollen 

percentages for tree genera that commonly benefit from fire (pine, 

oak, chestnut, and hickory).

The longest records (fig. 6.11A–D) are from four of Lynch and 

Clark’s (2002) sites and span most or all of the Holocene Epoch. 

None of the four records has the same charcoal pattern, but each 

shows that fire was present through the Holocene. Fire activity 

does not seem to have responded strongly to changes in human 

activity except at Pine Swamp (fig. 6.11A) on the Appalachian 

Plateau in Maryland, where charcoal peaked sharply during 

the last 500 years, consistent with intensification of indigenous 

agriculture and with European settlement. The Pink Beds Bog 

site (fig. 6.11B) in the southern Blue Ridge Mountains of North 

Carolina indicates an opposing pattern in which burning was 

more pronounced during the Archaic Period than later; whether 

this apparent shift reflects changes in anthropogenic burning 

or Holocene shifts in climate and vegetation is not known. The 

coincidence between the decline in charcoal accumulation and 

the decline in chestnut pollen percentages between 5,000 and 

3,000 BP led Lynch and Clark (2002) to suggest that fire has 

played an important role in shaping Appalachian chestnut forests. 

The two remaining sites in Virginia, Browns Pond (fig. 6.11C) 

and Spring Pond (fig. 6.11D), display no obvious long-term 

temporal trends, although they indicate considerable variability 

between successive 500-year intervals. Pollen records from 

the two Virginia sites suggest that after the shift from boreal 

to temperate forest in the early Holocene, oak dominance was 

favored for much of the Holocene. 

Two additional sites have yielded records spanning much of the 

Holocene—Devil’s Bathtub and Cliff Palace Pond. As discussed 

above, at Devil’s Bathtub (fig. 6.11E), charcoal accumulation 

declined in the early Holocene and then leveled off. At the Cliff 

Palace Pond site (fig. 6.11F) on the Appalachian Plateau of 

Kentucky, Delcourt and others (1998) retrieved a sediment core 

from a pond near rock shelters that had been used by aboriginal 

people since the early Archaic Period or before. They analyzed 

microscopic charcoal fragments on pollen slides, including 

fragments with mean diameters as small as 0.0004 inch (9 μm). 

Fire activity appears to have been relatively high during the early 

and middle Archaic Period and to have declined dramatically 

in the late Archaic. The area became an important center for 

plant husbandry and domestication during the late Archaic and 

early Woodland Periods, and as human use of the landscape 

intensified, fire activity increased. These fires are thought to have 

contributed to the increase in oak, pine, and chestnut (Delcourt 

and others 1998).

Similarly, Delcourt and Delcourt (1997) found charcoal 

evidence of fire through the past 4,000 years at Horse Cove 

Bog (fig. 6.11G) near the Blue Ridge escarpment of western 

North Carolina, based on microscopic charcoal on pollen slides 
Fire History of the Appalachian Region: A Review and Synthesis 83

(> 0.0004 inch, or 9 μm). They attributed the prehistoric fires 

to aboriginal burning because several important archaeological 

sites dot the landscape and because the extremely wet climate 

along the escarpment does not favor lightning ignitions, at least 

currently. These fires appear to have maintained oak, chestnut, 

and pine on this landscape, where in the absence of fire the moist 

environment would favor shade-tolerant mesophytic tree species. 

The recent charcoal spike at this site was ascribed to European 

settlement and to an increase in erosion (and hence charcoal 

delivery) following widespread land clearance (Delcourt and 

Delcourt 1997).

Any overall conclusions based on the patterns observed at the 

seven sites with charcoal records spanning many millennia must 

be made with caution because of the uncertainties that arise from 

low rates of sedimentation and low numbers of radiocarbon or 

other dates at several of the sites. Questions also exist concerning 

how to compare the evidence from charcoal with the more highly 

resolved records of fire history derived from the study of firescarred trees in the Appalachian region. Much of the research on 

reconstructing long-term fire history from charcoal, especially 

in terms of separating background charcoal and charcoal 

peaks to estimate MFIs, has been carried out in areas of North 

America where the fire regime is characterized by catastrophic 

crown fires that occur at long intervals. In these situations, a 

decline in charcoal influx and in the frequency of charcoal peaks 

indicates reduced fire frequency and increased MFIs. However, 

reductions in overall charcoal influx and increased spacing 

between charcoal peaks could also result from a shift toward a 

fire regime of increased surface fires. These surface fires may 

burn more frequently but result in lower production and transport 

of charcoal particles to sedimentary basins than more severe, 

convective-driven crown fires (Whitlock and Larsen 2001). 

Another important question is what is indicated if a site yields 

extremely small amounts of charcoal, as at Spring Pond. Lynch 

and Clark (2002) interpreted the Spring Pond record to indicate 

that fires were rare or absent over the past 20,000 years. This 

interpretation is at odds with the frequent burning during the 

last three centuries documented by the analysis of fire-scarred 

trees growing on the slopes of Kelley Mountain, approximately 

five miles away within the Blue Ridge Mountains (see chapter 

4) (Aldrich and others 2014). Spring Pond is one of several 

ponds dotting a debris fan complex along the base of Kelley 

Mountain and associated ridges. The streams that drain the 

ridges flow onto the fans through channels incised into the fan 

surface, presumably transporting charcoal from the ridges onto 

the fans. But little sediment from the mountain slopes appears 

to be delivered to Spring Pond because it is a spring-fed pond 

that occupies an interfluvial position on a fan, hence the low 

sedimentation rate and the disconnection between charcoal and 

tree-ring records of fire history on the nearby mountain slopes. 

Such disconnections commonly appear where a lake or bog is not 

well positioned to receive charcoal (Whitlock and Larsen 2001), 

and they need to be taken into account when interpreting records.

The low charcoal levels for Spring Pond should not be interpreted 

to indicate that fire has been rare. In fact, fires probably swept 

frequently across the debris fans. The fans make up a relatively 

flat area adjacent to the floor of the Shenandoah Valley, where 

frequent fires likely maintained open woodlands and areas 

of savanna (Mitchell 1972). Fine, grass fuels may have also 

extended onto the fans. The combustion of these fuels would not 

have produced abundant macroscopic charcoal fragments of the 

size analyzed by Lynch and Clark (≥ 0.0071 inch, or 180 μm); 

hence their absence from the Spring Pond sediment core does not 

provide evidence for the rarity or absence of fire.

In the ideal situation for studies of sedimentary charcoal, the 

history of recent fires in the watershed is known from historic 

records or tree-ring analyses, making it possible to compare 

and calibrate the recent portion of the sediment charcoal record 

against the historic record of fires. If lake sediment charcoal 

cannot be calibrated against fire-scar or other records, Whitlock 

and Larsen (2001) advise that another site should be chosen 

for charcoal analysis. Several situations conspire against 

this ideal and recommendation in the Appalachian region. 

First, information is sparse or lacking on historic fires within 

watersheds with lakes or wetlands suitable for charcoal analyses. 

Second, lakes and wetlands suitable for charcoal analysis are 

few. And third, as noted by Whitlock and Larsen (2001), the 

technique of macroscopic charcoal analysis is heavily biased 

toward the detection of catastrophic crown fires, a type of fire that 

is limited in frequency and spatial extent in most Appalachian 

ecosystems today and may have been for many millennia. The 

surface fires that we reconstruct in tree-ring analyses, which 

produce less charcoal and smaller convective plumes than more 

severe crown fires, may not leave distinct peaks of charcoal in 

lake sediments. Instead, frequent surface fires may primarily 

contribute to background charcoal. Thus, even the availability 

of fire-scar studies within lake watersheds may not provide the 

calibration suggested by Whitlock and Larsen (2001). However, 

this possibility needs to be tested through paired studies of firescarred trees and lake sediments in Appalachian watersheds, a 

type of study that to our knowledge has not yet been undertaken, 

likely owing to the very few sites that might be amenable to such 

a study.

Bearing such uncertainties in mind, we can conclude at a 

minimum that fire has been present on Appalachian landscapes 

through the Holocene. Some of the graphs in fig. 6.11 show 

considerable temporal variations, but the fire histories examined 

are unique. Hart and Buchanan (2012) examined an overlapping 

set of sediment charcoal records from the Appalachian region 

and also found a lack of clear, ubiquitous patterns. Because 

most of the sediment charcoal records summarized here were 

based on the analysis of macroscopic charcoal, a signal of local 

fires, the absence of strong correlations between records is not 

surprising. We can expect that the history of burning over time in 

the Appalachian region was spatially variable, and the sediment 

charcoal records confirm this to be true. 
ARCH WOOD MISS HIST

0.014

0.012

0.010

0.008

0.006

0.004

0.002

0.000

0.014

0.012

0.010

0.008

0.006

0.004

0.002

0.000

20000 18000 16000 14000 12000 10000 8000 6000 4000 2000 0

Calibrated years BP

Lynch and Clark (2002) 

Pine Swamp, MD

Charcoal accumulation

(in 2 in -2 yr -1)

Sediment 

Charcoal

100

80

60

40

20

0

0.0020

0.0018

0.0016

0.0014

0.0012

0.0010

0.0008

0.0006

0.0004

0.0002

0.0000

20000 18000 16000 14000 12000 10000 8000 6000 4000 2000 0

Calibrated years BP

Charcoal accumulation

(in 2 in -2 yr -1)

Percentage of arboreal pollen

Sediment 

Charcoal ARCH WOOD MISS HIST

Pine Oak Chestnut Hickory Lynch and Clark (2002)

Pink Beds Bog, NC

100

80

60

40

20

0

20000 18000 16000 14000 12000 10000 8000 6000 4000 2000 0

Calibrated years BP

Charcoal accumulation

(in 2 in -2 yr -1)

Percentage of upland pollen

Sediment 

Charcoal ARCH WOOD MISS HIST

Pine Oak Chestnut Hickory Lynch and Clark (2002)

Browns Pond, VA

0.024

0.020

0.016

0.012

0.008

0.004

0.000

(A)

(B)

(C)

84 Chapter 6. Appalachian Fire History as Reconstructed from Charcoal

Figure 6.11—Estimates of charcoal levels (black bars) and tree pollen (colored lines) for 500-year 

intervals at sites with multimillennial records: (A) Pine Swamp, (B) Pink Beds Bog, (C) Browns Pond, 

(D) Spring Pond, (E) Devil’s Bathtub, (F) Cliff Palace Pond, and (G) Horse Cove Bog. Pollen data 

are from the same study as the charcoal data except for two sites: Browns Pond, with pollen data from 

Kneller and Peteet (1993), and Spring Pond, with pollen data from Craig (1969). Background shading 

as in figure 6.08. ARCH = Archaic Period, WOOD = Woodland Period, MISS = Mississippian Period, 

HIST = Historic Period. (continued on next page)
100

80

60

40

20

0

20000 18000 16000 14000 12000 10000 8000 6000 4000 2000 0

Calibrated years BP

Charcoal accumulation

(in 2 in -2 yr -1)

Percentage of arboreal pollen

Sediment 

Charcoal ARCH WOOD MISS HIST

Pine Oak Chestnut Hickory Lynch and Clark (2002)

Spring Pond, VA

6*10-4

5*10-4

4*10-4

3*10-4

2*10-4

1*10-4

0*10 0

MISS HIST

Charcoal accumulation

(in 2 in -2 yr -1)

ARCH WOOD Sediment 

Charcoal

0.50

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Clark and others (1996)

Devil’s Bathtub, NY

20000 18000 16000 14000 12000 10000 8000 6000 4000 2000 0

Calibrated years BP

100

80

60

40

20

0

20000 18000 16000 14000 12000 10000 8000 6000 4000 2000 0

Calibrated years BP

Charcoal accumulation

(in 2 in -2 yr -1)

Percentage of upland pollen

Sediment 

Charcoal ARCH WOOD MISS HIST

Pine Oak Chestnut Hickory Delcourt and others (1998)

Cliff Palace Pond, KY

0.05

0.04

0.03

0.02

0.01

0.00

100

80

60

40

20

0

20000 18000 16000 14000 12000 10000 8000 6000 4000 2000 0

Calibrated years BP

Charcoal accumulation

(in 2 in -2 yr -1)

Percentage of upland pollen

Sediment 

Charcoal ARCH WOOD MISS HIST

Pine Oak Chestnut Hickory Delcourt and Delcourt (1997)

Horse Cove Bog, NC

0.30

0.25

0.20

0.15

0.10

0.05

0.00

(D)

(E)

(F)

(G)

Fire History of the Appalachian Region: A Review and Synthesis 85

Figure 6.11 (continued)—(D) Spring Pond, 

(E) Devil’s Bathtub, (F) Cliff Palace Pond, 

and (G) Horse Cove Bog. Pollen data are 

from the same study as the charcoal data 

except for two sites: Browns Pond, with 

pollen data from Kneller and Peteet (1993), 

and Spring Pond, with pollen data from Craig 

(1969). Background shading as in figure 6.08. 

ARCH = Archaic Period, WOOD = Woodland 

Period, MISS = Mississippian Period, 

HIST = Historic Period. 
86 Chapter 6. Appalachian Fire History as Reconstructed from Charcoal

The spatial and temporal variability in fire in the Appalachian 

region documented by the sediment charcoal records raises the 

question of how strongly these variations relate to climate and 

environmental factors and trends, as compared to prehistoric 

human activities that purposefully or inadvertently increased or 

decreased wildland fires. From the records, we can conclude that 

fire activity increased at some sites because of anthropogenic 

burning during the Woodland or Mississippian Archaeological 

Periods. But teasing apart human activity versus climate and 

environmental change as drivers of past fire requires more 

research. Specifically, we need a larger number of carefully 

sampled and analyzed charcoal records, coupled with information 

on past climate, vegetation, and human activity that is derived 

from analyses of additional proxies in the sediment cores or other 

paleoenvironmental archives, and from local archaeological 

investigations.

A Multimillennial View of Fire History at Coarse 

Resolution from Soil Charcoal

Soil charcoal analyses that include radiocarbon dating of 

fragments have been conducted in the Appalachian region only 

in the last decade, with data available from just five sites: four in 

the southern Blue Ridge Mountains and one on the Appalachian 

Plateau in Tennessee (fig. 6.07). At Wine Spring Creek in North 

Carolina (fig. 6.12A), Fesenmyer and Christensen (2010) dated 

83 charcoal fragments from 18 soil cores collected along a 

topographic gradient (dry ridge to moist cove). At three sites 

in Great Smoky Mountains National Park (figs. 6.12B–D), 

Underwood (2013) obtained 133 radiocarbon dates for charcoal 

fragments in 48 soil cores. These cores were collected from 

the same sites where LaForest (2012) sampled yellow pines to 

develop fire-scar records. 

The charcoal dates for the Blue Ridge Mountains show a similar 

temporal distribution across the four study sites (fig. 6.12), with 

more charcoal from the last millennium than the previous three 

millennia. The rarity of charcoal fragments with ages > 1,000 BP 

may in part reflect the gradual breakdown of charcoal fragments 

over time (Horn and Underwood 2014). Therefore, the graphs 

should not be interpreted to necessarily indicate a steady or 

exponential increase in fire activity over time. The records 

indicate, instead, that fire has burned these particular mountain 

slopes through much of the Holocene. The site specificity of soil 

charcoal is one of its main advantages over sediment charcoal. 

At Wine Spring Creek, it is possible to infer that fires have a 

history of burning the entire topographic gradient, which today 

includes mesophytic cove forest as well as xerophytic oak–pine 

forest on the upper slopes. For the Great Smoky Mountains 

sites, Underwood (2013) taxonomically identified the charcoal 

fragments to provide evidence of the vegetation that burned 

in past fires. He found the most abundant charcoal type in his 

samples to be charcoal from the yellow pine group, which 

suggests that the long history of burning has helped maintain 

yellow pine populations for thousands of years. However, 

charcoal from oaks, chestnut, American elm (Ulmus americana), 

white pine, and hemlock was also present in the samples. The 

presence of charcoal from these taxa suggests past intervals of 

relatively low fire activity that enabled less fire-resistant trees to 

occupy the slopes, followed by a resurgence of fires that burned 

these tree taxa.

Some interpretations of broad temporal changes in fire activity 

may be possible from the soil charcoal studies conducted in the 

southern Blue Ridge Mountains. Underwood (2013) noted peaks 

in soil charcoal dates in the late Archaic Period (figs. 6.12B–D) 

and tentatively linked them to a late Archaic cultural shift from 

hunting and gathering to cultivation. Similarly, Fesenmyer 

and Christensen (2010) noted that their charcoal record begins 

in the late Archaic Period, and their charcoal dates from this 

interval may indicate an increase in burning associated with the 

cultural transition. They also interpreted an increase in charcoal 

dates around 1,000 years ago as a potential reflection of more 

widespread burning associated with the maize-based agriculture 

of the Mississippian Period.
45

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Fesenmeyer and Christensen (2010)

Wine Spring Creek, NC MISS HIST

10000 8000 6000 4000 2000 0

Calibrated years BP

Percentage of charcoal

fragments at oak-pine sites

ARCH WOOD

Soil Charcoal

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MISS HIST

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Calibrated years BP

Percentage of

charcoal fragments

Soil Charcoal ARCH WOOD

Underwood (2013)

Gold Mine Trail, TN

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MISS HIST

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Calibrated years BP

Percentage of

charcoal fragments

Soil Charcoal ARCH WOOD

Underwood (2013)

Pine Mountain, TN

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0

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MISS HIST

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Calibrated years BP

Percentage of

charcoal fragments

Soil Charcoal ARCH WOOD

Underwood (2013)

Rabbit Creek Trail, TN

(A)

(B)

(C)

(D)

Fire History of the Appalachian Region: A Review and Synthesis 87

Figure 6.12—Estimates of charcoal 

levels for 500-year intervals at (A) Wine 

Spring Creek, (B) Gold Mine Trail, 

(C) Pine Mountain, and (D) Rabbit 

Creek Trail. ARCH = Archaic 

Period, WOOD = Woodland Period, 

MISS = Mississippian Period, 

HIST = Historic Period. 
88 Chapter 6. Appalachian Fire History as Reconstructed from Charcoal

Additional soil charcoal data are available from the work of Hart 

and others (2008), who examined macroscopic charcoal in 10 soil 

cores collected in a mixed hardwood forest on the Cumberland 

Plateau of Tennessee. This project was completed before the 

studies in the Blue Ridge Mountains, when the importance of 

dating individual charcoal fragments was not yet recognized. Five 

samples were submitted for radiocarbon determination, four of 

which consisted of multiple charcoal fragments from the same 

depth increment of a particular soil core. Calibrated ages for 

the samples indicated fires at the site as early as about 7,000 cal 

yr BP, but this result may underestimate the age of the earliest 

fire if the charcoal fragments in the oldest sample were a mix 

of older and younger charcoal particles. The study by Hart and 

others (2008) was the first to attempt taxonomic identification 

of charcoal in Appalachian soils. Twelve of the larger charcoal 

fragments recovered were examined and determined to be from 

trees with a diffuse porous growth-ring structure, possibly sugar 

maple, red maple, American beech, or yellow-poplar. These trees 

are present today, but the site is dominated by mixed oak and 

hickory species that do not have this growth-ring structure. The 

representation of diffuse porous taxa in the charcoal assemblages 

suggested that one or more of these species were present at the 

time of past fires. 

CONCLUSIONS AND IMPLICATIONS

Charcoal-based fire histories help to contextualize the fire-scar 

studies discussed in chapter 4; they also extend our understanding 

of Appalachian fire history beyond the temporal limits of tree-ring 

research. Charcoal in sediment cores from Appalachian lakes and 

wetlands does not provide the temporal resolution of fire scars 

and therefore cannot offer guidance to resource managers about 

appropriate intervals or seasons for controlled burning. In the 

best cases, however, where macroscopic charcoal is analyzed in 

cores from basins with rapid sedimentation, results may indicate 

whether fire history reconstructions from fire scars at nearby 

sites may pertain to centuries or millennia that precede the treering record. The Trout Pond charcoal record (fig. 6.08A), for 

example, suggests that the frequent surface burning documented 

by fire-scar studies from the central Ridge and Valley province 

(e.g., Aldrich and others 2010, 2014; Hessl and others 2011) 

was typical for at least the past millennium. Similarly, it seems 

reasonable to infer from the collocated soil charcoal records 

(Underwood 2013) that the historic regime of frequent burning 

established by LaForest (2012) from fire-scar chronologies in the 

Great Smoky Mountains has characterized the sites for millennia.

Such inferences should be made cautiously, of course, because 

charcoal sampled in soils and sediments does not offer the 

annual precision of fire-scarred trees. Most Appalachian charcoal 

records have only low or modest resolution. Some of this is a 

consequence of the sedimentation rate in the basin selected, 

which provides a constraint on the resolution that can be 

achieved. In other cases, resolution could be improved through 

additional radiocarbon or lead-210 analyses. A clear need exists 

to develop additional multimillennial fire chronologies from 

sediment and soil charcoal studies across the Appalachian region, 

to extend the high-resolution records that we and others are 

developing from tree-ring analyses.

In the interim, the charcoal records at hand demonstrate 

unequivocally that fire has a long history in the Appalachian 

Mountains. This history extends through most of the Holocene, 

and it varies over space and time as we would expect given the 

spatial heterogeneity of the landscape and past changes in human 

activity and climate. For at least some locations, the amount of 

burning seems to have risen when human populations increased 

and intensified their land use. Finally, soil charcoal identification 

and pollen analyses of sediment profiles provide some evidence 

that Holocene fires helped maintain fire-favored trees such as 

oak, chestnut, and yellow pine in the Appalachian region.
Fire History of the Appalachian Region: A Review and Synthesis

89

Chapter 7. 

Summary: The Picture That Emerges 

of Appalachian Fire History

The vegetation of the Appalachian region (fig. 1.01) has been 

shaped by a history of fire. Evidence of this fire history has been 

obtained from various sources, and it suggests that the conceptual 

model of Appalachian fire history outlined by Brose and others 

(2001) (fig. 1.02) is generally correct. Fires had recurred at short 

intervals for centuries before they became mostly excluded 

beginning in the early to middle 20th century. In fact, fire has 

played an important role in the development of Appalachian 

vegetation for millennia.

The model of Brose and others (2001) diverges from empirical 

observations in predicting anomalously high levels of fire 

activity during the industrial logging episode of the late 19th 

through early 20th centuries. This period did not actually see 

more frequent burning than previous centuries, at least in areas 

covered by oak- and pine-dominated forests of the central and 

southern Appalachian Mountains. We have therefore suggested 

a modification of the model that does not include a peak in fire 

activity during the logging episode (fig. 4.18). Nonetheless, a 

pattern resembling the original model applies in some places, 

notably the northern edge of the study region where the northern 

hardwoods forest did not burn regularly until human land use 

intensified during the 19th century.

The evidence concerning fire and vegetation history of the 

Appalachian region is consistent with the fire-oak hypothesis 

(e.g., Lorimer and others 1994, Nowacki and Abrams 2008), 

which proposes that frequent surface fires maintained an 

open canopy and understory that enabled the establishment of 

oaks (and, historically, American chestnut) and inhibited the 

recruitment of mesophytic competitors. These mesophytic species 

lack the thick bark, large hypogeal roots, and other traits that 

favored the survival of oaks. Young oaks, by growing large roots 

and sprouting repeatedly after top-kill, would have persisted 

through multiple cycles of burning until they were able to bolt to 

a more fire-resistant size during the occasional fire-free interval 

of abnormal length, i.e., a length on the order of 10–15 years. 

Burning also favored yellow pines, particularly on relatively dry, 

infertile sites with sandy, well-drained soils on ridgetops and 

south- or west-facing slopes. On these sites, post-fire vegetation 

recovery was slow, and fires often burned with greater severity 

than elsewhere. Fire essentially operated as a filter on tree 

establishment within fire-prone sites by destroying the seedlings 

of fire-sensitive species. These species undoubtedly dispersed 

seeds onto the flammable mountain slopes, but to little avail. 

They were relegated to mesic coves, riparian zones, talus slopes, 

and other sites that were sheltered from frequent burning. In this 

way, fires contributed to the topographic patterning of vegetation 

over mountainous terrain.

The legacy of the past fire regime still endures in the form 

of widespread oak and yellow pine dominance in forests of 

the Ridge and Valley province, the Blue Ridge Mountains, 

the Piedmont, and parts of the Appalachian Plateau. In fact, 

a montane oak–pine vegetation complex covers as much as 

three-fourths of the total land area in the National forests that 

sprawl over the Ridge and Valley and the Blue Ridge provinces. 

This vegetation is by no means a consequence of past fires 

alone—human land use, climate, soil, and other factors also 

come into play. With respect to land use, for example, oak and 

pine recruitment was favored by the sequence of land clearance 

and subsequent abandonment that unfolded during the one to 

two centuries that followed European settlement. But fire was 

an essential factor without which oak- and pine-dominated 

ecosystems could never have grown to cover such extensive 

areas. Even before European settlement, oak and pine were the 

most abundant tree genera in the Ridge and Valley, Blue Ridge, 

and Piedmont provinces, according to multiple vegetation proxies 

(figs. 3.02, 5.03, 6.11).

The Appalachian Plateau had less oak and pine. That is not to say 

these genera were absent, however. Oak was relatively important 

in witness tree and pollen records from the plateau (figs. 3.02, 

6.11). Nonetheless, the Appalachian Plateau was less extensively 

covered with pyrogenic vegetation, and this regional vegetation 

gradient appears to have paralleled a regional gradient in past 

fire frequency. Predictive models of pre-exclusion fire interval 

(Frost 1998, Guyette and others 2012) indicate that the central 
90 Chapter 7. Summary: The Picture That Emerges of Appalachian Fire History

and eastern sections of the Appalachian Plateau saw longer fire 

intervals than the rest of the Appalachian region (figs. 4.20, 4.21), 

a geographical pattern that reflects regional gradients in climate, 

terrain, and vegetation.

This broad pattern of fire frequency is consistent with fire-scar 

data (figs. 4.22–4.25), suggesting that the predictive model 

developed by Guyette and others (2012) is useful for estimating 

and mapping past fire intervals for areas that lack fire-scarred 

trees or other empirical records. However, comparing observed 

and predicted fire intervals for specific study sites reveals that the 

model overestimates the length of fire-free intervals (fig. 4.26). 

This mismatch indicates that the mean fire interval predicted by 

the model of Guyette and others (2012) should be viewed as a 

conservative estimate of pre-exclusion fire activity at a site.

The divergence between observed and predicted fire intervals 

probably reflects factors that are not readily incorporated 

into a predictive model. Two such factors seem especially 

important—spatial contingencies and fire-fuel feedbacks. Spatial 

contingencies would have emerged because fire is a contagious 

disturbance that spreads across a landscape (Peterson 2002). 

Its occurrence at a specific point did not depend solely on the 

environmental conditions at the point but also on the flammability 

of the surrounding landscape through which fires were conveyed 

to that point. Contingencies likely played an important role in the 

Ridge and Valley province and Blue Ridge Mountains because the 

relatively cool, moist sites at middle elevations were connected 

to warmer, drier, more flammable sites at lower elevation. The 

spread of fire across a landscape ultimately would have conveyed 

fire to every point on the landscape at a higher frequency than 

would be expected from site conditions alone.

Fire spread was probably abetted by fire-fuel feedbacks that 

maintained a flammable vegetation structure. Open forest/

woodland canopies with continuous fine fuels comprising grass, 

small shrubs, and oak and pine litter would have favored rapid 

drying of fuel and ready ignition by people or lightning. This 

flammable fuel structure would have enabled fires to spread 

quickly across a landscape to encompass many stands. Individual 

fires must have burned much larger acreages than observed at 

present, thereby maintaining a short fire interval at individual 

sites through which the fires passed. In turn, this frequent burning 

would have favored the development of a flammable, selfperpetuating vegetation structure.

Appalachian vegetation has been shifting in structure and 

composition as a consequence of fire exclusion. In its early phase, 

fire exclusion allowed a pulse of tree establishment by xerophytic 

and mesophytic species alike (figs. 5.03–5.04). As mesophication 

progressed, however, the establishment of oak and yellow pine 

diminished. The formerly open, flammable woodlands have 

transitioned toward dense forest stands with canopy dominants 

that were recruited under one fire regime but with an understory 

of shrubs and mesophytic trees that emerged under a new fire 

regime. As the overstory dominants die and are replaced by the 

understory species, former vegetation patterns are disappearing. 

Forests of fire-intolerant species that can regenerate in shaded, 

closed-canopy environments are expanding from formerly firesheltered refugia onto the broad mountainous landscape that once 

supported forests and woodlands of oak, chestnut, and yellow 

pine (fig. 5.07). With these vegetation changes will also come 

a further reduction in the general flammability of the landscape 

and a concomitant decline in the frequency of fire.

The departures from past conditions have motivated resource 

managers to implement prescribed burning and other measures, 

such as mechanical thinning, to restore pyrogenic vegetation 

on the National forests, National parks, and State and private 

conservation lands across the Appalachian region. Our synthesis 

of fire history underscores the need to continue these restoration 

projects and to expand them where feasible, possibly by using 

landscape-level burning where appropriate to mimic the largeextent fires that once occurred, especially in the Ridge and 

Valley province and the Blue Ridge Mountains. Our synthesis 

also suggests areas for further research. These research needs 

include an expansion of fire history studies to cover parts of the 

Appalachian region that are underrepresented in terms of fire 

history research; a better characterization of landscape patterns 

of burning; and more detailed information on such topics as 

the seasonality of past fires, the weather conditions that favor 

lightning ignitions, and the history of shrub establishment in 

forest understories during the era of fire exclusion.

As fire history research is expanded geographically and deepened 

topically, new findings will no doubt suggest refinements to our 

portrayal of Appalachian fire history and to the management 

needs implied by this portrait. However, we do not anticipate any 

changes to the general picture that emerges from our synthesis of 

fire history—that before the exclusion era, fires burned frequently 

and widely across broad swaths of the Appalachian Mountains.
Fire History of the Appalachian Region: A Review and Synthesis

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Agriculture, Forest Service, Southern Research Station. 97 p.

The importance of fire in shaping Appalachian vegetation has become increasingly 

apparent over the last 25 years. This period has seen declines in oak (Quercus) 

and pine (Pinus) forests and other fire-dependent ecosystems, which in the 

near-exclusion of fire are being replaced by fire-sensitive mesophytic vegetation. 

These vegetation changes imply that Appalachian vegetation had developed 

under a history of burning before the fire-exclusion era, a possibility that has 

motivated investigations of Appalachian fire history using proxy evidence. 

Here we synthesize those investigations to obtain an up-to-date portrayal of 

Appalachian fire history. We organize the report by data type, beginning with 

studies of high-resolution data on recent fires to provide a context for interpreting 

the lower-resolution proxy data. Each proxy is addressed in a subsequent chapter, 

beginning with witness trees and continuing to fire-scarred trees, stand age 

structure, and soil and sediment charcoal. Taken together, these proxies portray 

frequent burning in the past. Fires had occurred at short intervals (a few years) for 

centuries before the fire-exclusion era. Indeed, burning has played an important 

ecological role for millennia. Fires were especially common and spatially 

extensive on landscapes with large expanses of oak and pine forest, notably in the 

Ridge and Valley province and the Blue Ridge Mountains. Burning favored oak 

and pine at the expense of mesophytic competitors, but fire exclusion has enabled 

mesophytic plants to expand from fire-sheltered sites onto dry slopes that formerly 

supported pyrogenic vegetation. These changes underscore the need to restore firedependent ecosystems.

Keywords: Age structure, Appalachian Mountains, charcoal, fire history, fire 

regime, fire scars, witness trees.
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