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Fire Ecology Volume 12, Issue 2, 2016
doi: 10.4996/reecology.1202065
Stambaugh et al.: Scale Dependence of Fire Regimes
Page 65
ReseaRch aRticle
SCALE DEPENDENCE OF OAK WOODLAND HISTORICAL FIRE INTERVALS:
CONTRASTING THE BARRENS OF TENNESSEE AND
CROSS TIMBERS OF OKLAHOMA, USA
Michael C. Stambaugh1*, Richard P. Guyette1, Joseph M. Marschall1, and Daniel C. Dey2
1 Department of Forestry, University of Missouri,
203 ABNR Building, Columbia, Missouri 65211, USA
2 USDA Forest Service, Northern Research Station, University of Missouri,
202 ABNR Building, Columbia, Missouri 65211, USA
*Corresponding author: Tel.: +1-573-882-8841; e-mail: stambaughm@missouri.ed
ABSTRACT
Characterization of scale dependence
of re intervals could inform interpre-
tations of re history and improve re
prescriptions that aim to mimic histor-
ical re regime conditions. We quan-
tied the temporal variability in re
regimes and described the spatial de-
pendence of re intervals through the
analysis of multi-century re scar re-
cords (8 study sites, 332 trees, 843 re
scars) derived from two historically
post oak (Quercus stellata Wangenh.)
woodland landscapes. Despite large
differences in re environment condi-
tions, study sites (~1 km2) burned fre-
quently (mean re interval [MFI] ≤10
yr) before Euro-American settlement
(pre-EAS), with sites in Tennessee
showing higher overall re frequency
than sites in Oklahoma, USA. Pre-
EAS MFIs decreased exponentially
with increasing spatial extent from in-
dividual trees (~1 m2) to landscapes
(~100 km2). The relationship between
MFI and spatial extent may help to
explain how historical observations of
annual burning could be recorded in
woodlands, when experimental stud-
ies suggest that this is too frequent for
RESUMEN
La caracterización de la dependencia de la es-
cala de los intervalos de fuego podría informar
sobre interpretaciones de la historia del fuego y
mejorar prescripciones que apunten a imitar
condiciones históricas del régimen de incen-
dios. Nosotros cuanticamos la variabilidad
temporal en los regímenes de fuego y describi-
mos la dependencia espacial de intervalos de
fuego a través del análisis de archivos de cica-
trices de fuego por muchas centurias (8 sitios
de estudio, 332 árboles, 843 cicatrices de fue-
go) derivados de dos paisajes históricos de ar-
bustales de roble de los postes (Quercus stella-
ta Wangenh). A pesar de las grandes diferen-
cias en las condiciones ambientales de fuego,
los sitios de estudio (~1 km2) se quemaron fre-
cuentemente (intervalo promedio de fuego
[MFI] ≤ 10 años) antes del asentamiento eu-
ro-americano (pre-EAS), mostrando una fre-
cuencia general de fuegos en los sitios de Ten-
nessee más alta que en los de Oklahoma,
EEUU. Los MFIs en el pre-EAS decreció en
forma exponencial con el grado de aumento es-
pacial desde árboles individuales (~1 m2) hasta
paisajes (~100 km2). La relación entre en MFI
y la extensión espacial puede ayudar a explicar
como observaciones históricas de quemas
anuales podrían ser recopiladas en arbustales,
cuando estudios experimentales sugieren que
Fire Ecology Volume 12, Issue 2, 2016
doi: 10.4996/reecology.1202065
Stambaugh et al.: Scale Dependence of Fire Regimes
Page 66
tree recruitment. Further investiga-
tions of spatial dependence of re in-
tervals would improve our ability to
relate historical and experimental re
data to present day re prescriptions,
and vice versa.
esto es muy frecuente para el reclutamiento de
árboles. Otras investigaciones de la dependen-
cia espacial de los intervalos de fuego podrían
mejorar nuestra habilidad para relacionar datos
históricos y experimentales de fuego a prescrip-
ciones actuales de fuego y vice versa.
Keywords: management, oak woodland, pyrodiversity, restoration, spatial extent, succession
Citation: Stambaugh, M.C., R.P. Guyette, J.M. Marschall, and D.C. Dey. 2016. Scale depen-
dence of oak woodland historical re intervals: contrasting The Barrens of Tennessee and Cross
Timbers of Oklahoma, USA. Fire Ecology 12(2): 65–84. doi: 10.4996/reecology.1202065
INTRODUCTION
Nineteenth- to twentieth-century trends of
oak (Quercus spp. L.) woodland communities
in the eastern US overwhelmingly show transi-
tion to more closed-canopy conditions and
re-intolerant tree species (Dyer 2001, Nowac-
ki and Abrams 2008, Hanberry et al. 2014).
Prior to Euro-American settlement (pre-EAS)
and logging effects, re was considered the
primary disturbance that maintained oak wood-
land communities. Interest in woodland resto-
ration and management is increasing, not only
because of historical prevalence and modern
rarity, but also due to the multiple ecological
benets resulting from re restoration com-
pared to re suppression. Recently, research
has focused on how re treatments may be in-
corporated into silvicultural systems (Ryan et
al. 2013, Brose 2014, Dey and Kabrick 2015).
Detailed and spatially explicit information is
needed about the re ecology of woodlands,
including how species and ecosystem function
respond to specic re regime conditions, and
how or if tree recruitment can be sustained
through repeated, long-term burning. Speci-
cally, understanding the scale dependencies of
re intervals would improve the ability to
crosswalk between sources that characterize
woodlands such as historical data, experimen-
tal data, and present day re monitoring. Addi-
tionally, quantifying the variability in re inter-
vals across spatial and temporal scales may in-
form us about their relative importance as re-
lated to oak woodland development.
Oak woodlands are highly variable forest
communities with open canopies ranging from
30 % to 100 % closure; sparse midstories; and
a dense ground ora rich in forbs, grasses, and
sedges (Nelson 2005). Historically, wood-
lands existed in ecoregions throughout the
eastern deciduous forest (Braun 1950, Bailey
1997), including being embedded components
of glades, barrens, and oak-pine ecosystems,
accompanying shortleaf pine (Pinus echinata
Mill.), longleaf pine (P. palustris Mill.), red
pine (P. resinosa Aiton), and pitch pine (P.
rigida Mill.). Mature canopy heights may
range from 6 m to 27 m depending on site con-
ditions. Nelson (2005) identied 18 different
oak woodland communities in Missouri, USA,
and vascular plant species richness can exceed
200 species ha-1. Diverse species composi-
tions and open canopy structures of woodlands
are attributed to repeated and relatively fre-
quent res (Olmstead 1857, Swallow 1859),
although effects of other interacting distur-
bances and drought also promote canopy
openness (McEwan et al. 2011). Oak wood-
lands with these characteristics occurred
throughout North America pre-EAS despite
being relatively rare today (Hanberry et al.
2014). During the twentieth century to the
present, rates of forest transitions from open-
to closed-canopy conditions have varied by re-
gion and species assemblages (Guyette et al.
Fire Ecology Volume 12, Issue 2, 2016
doi: 10.4996/reecology.1202065
Stambaugh et al.: Scale Dependence of Fire Regimes
Page 67
2003, DeSantis et al. 2011, Cocking et al.
2012, Stambaugh et al. 2014a). In long-un-
burned areas with minimal ground ora diver-
sity, the seedbank often evidences relict wood-
land conditions through its diversity and the
site requirements of seedbank species
(Hutchinson et al. 2005, Waldrop et al. 2008,
Kinkead et al. 2013).
For these reasons and others, re is in-
creasingly considered in silvicultural systems
and ecological restoration (Albrecht and Mc-
Carthy 2006, Dey and Schweitzer 2014,
Kabrick et al. 2014). Benets of re treat-
ments and woodland conditions are diverse
and arguably critical to sustaining the oak eco-
system, including enhancing oak regeneration
(Arthur et al. 2012, Brose et al. 2013); increas-
ing understory plant species cover and rich-
ness (Hutchinson et al. 2005, Ratajczak et al.
2012, McCord et al. 2014); and improving di-
versity of native insects (Wood et al. 2011),
birds (Reidy et al. 2014), and mammals
(McShea et al. 2007, Starbuck et al. 2015). At
larger scales, other benets of woodlands may
be realized, such as improved wildlife diversi-
ty through increasing early-successional habi-
tat (Thompson and DeGraff 2001), decreased
hazardous fuel loads, and increased climate
change resilience (Brandt et al. 2014).
Incorporating re science into manage-
ment faces many challenges, particularly in
the eastern US. Overall, re’s role in science,
land management, and society is poorly under-
stood and not well-founded (Pyne 2007).
Compared to other natural sciences (e.g., for-
estry, wildlife, hydrology, botany, atmospheric
science), re research and professional schol-
arship has lagged behind and has not been of
primary interest, despite being a linking theme.
In eastern hardwood forests, challenges and
varying perspectives exist related to incorpo-
rating re into forest management (Packard
1993, Matlack 2013, Stambaugh et al. 2015).
A primary point of contention is that promot-
ing re use, particularly in hardwoods, can be
perceived as inherently in conict with other
forest management objectives (i.e., re pre-
vention, wood ber production, and human
health promotion; Weldon 1996).
Historical re regimes of eastern US oak
woodlands vary at spatial scales from land-
scapes to regions (Guyette et al. 2003, 2006;
Stambaugh et al. 2014b). Through time, his-
torical re intervals within eastern oak wood-
lands can vary by an order of magnitude with-
in the spatial extent of study sites (e.g., 1 km2).
When managing for woodland conditions with
re, it is not clear whether maintenance of
woodland structures should focus on temporal
or spatial variability in re (or some combina-
tion). Understanding the historical distribu-
tion of woodlands, how re regimes varied
across landscapes, and how vegetation re-
sponded to re regime departures would bene-
t understanding their successional pathways
and designing management systems. Fire dis-
turbance properties are often simplied by dis-
regarding variability in metrics and how they
change with scale (Falk et al. 2007). To char-
acterize the temporal variability in re regimes
and to describe the spatial dependence of re
intervals, we analyzed eight multi-century re
scar records from two historically post oak
(Quercus stellata Wangenh.)-dominated wood-
land landscapes. The objectives of this study
were to: 1) reconstruct and contrast historical
re regime characteristics of sites within two
different landscapes using re scar analysis
and, 2) quantify the effect of spatial scale of
observation on re frequency. With this infor-
mation, we discuss the implications for histori-
cal data interpretation and oak woodland re
management. We expect that further under-
standing scaling theory of re regimes will in-
form re management decisions such as plan-
ning and employing burn treatments with char-
acteristics (e.g., frequency, size, location, se-
verity, patchiness) that historical res once
produced.
Fire Ecology Volume 12, Issue 2, 2016
doi: 10.4996/reecology.1202065
Stambaugh et al.: Scale Dependence of Fire Regimes
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METHODS
Study Landscape and Site Descriptions
Study landscapes consisted of the Wichita
Mountains Wildlife Refuge (WMWR) in the
Cross Timbers region of southwest Oklahoma,
USA, and Arnold Air Force Base (AAFB) in
The Barrens region of south-central Tennes-
see, USA (Figure 1, Table 1). These land-
scapes are approximately 1150 km apart with
contrasting physical, climatological, and bio-
logical properties (Figure 1). At each land-
scape, re scar history data were collected
from four sites across an approximately 100
km2 area historically dominated by post oak
woodlands. Data from the WMWR were col-
lected from 2006 to 2011 and are reported in
Stambaugh et al. (2009, 2014a), while data
from AAFB were collected from 2004 to 2005
and are reported here.
Figure 1. Study landscapes at the Wichita Mountains Wildlife Refuge, Oklahoma, USA, and Arnold Air
Force Base, The Barrens, Tennessee, USA.
Wichita Mountains, Oklahoma The Barrens, Tennessee
Ownership US Fish and Wildlife Service Arnold Air Force Base
Location 34° 45' 29" N, 98° 42' 21" W 35° 22' 16" N, 86° 5' 18" W
Terrain mountainous (310 m elevation) at to rolling (43 m elevation)
Temperature min./max. 9.7 °C to 23.8 °C a 8.6 °C to 21.1 °C b
Annual precipitation 78 cm a 142 cm b
Land types woodlands, grasslands, rock outcrops forested uplands, wetlands
Substrate rhyolite, cobbly limestone
Climate semi-arid and humid continental humid continental
Surrounded by Osage Plains Nashville Basin and Highland Rim
a Annual mean from 1912 to 2012.
b Annual mean from 1893 to 2004.
Table 1. Characteristics of the Wichita Mountains and The Barrens study landscapes.
Fire Ecology Volume 12, Issue 2, 2016
doi: 10.4996/reecology.1202065
Stambaugh et al.: Scale Dependence of Fire Regimes
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Dendrochronology and Fire Scar History
At both landscapes, four study sites (0.3
km2 to 1 km2) were established following
methods described in Stambaugh et al.
(2014a). Within the boundary of AAFB, re
scar history sites were established at Huckle-
berry Ridge (HCK), Rowland Creek Headwa-
ters (RCH), Saltwell Hollow (SLT), and Lemm
Swamp (LEM) (Figure 2). Site data from
WMWR are reported in Stambaugh et al.
(2014a). Sites were selected non-randomly
based on the availability of mature, re-
scarred post oaks and were spatially distribut-
ed to maximize distance between sites and in-
corporate variation in landscape characteris-
tics. Trees at each site were evaluated for
sampling adequacy based on bole soundness,
evidence of basal wounding, external tree con-
dition and architecture, and visual inspection
of basal cross-sectional surfaces. Attempts
were made to sample a range of tree sizes,
ages, and growth rates throughout the full peri-
od (more than 250 years; Guyette and Stam-
baugh 2004). Cross sections (10 cm to 30 cm
thick) were cut from the base of post oak trees
Figure 2. Hillshaded digital elevation model of landscape of Arnold Air Force Base (AAFB) and vicinity.
Locations of study areas are represented by triangles with site codes (HCK = Huckleberry Ridge, RCH =
Rowland Creek Headwaters, SLT = Saltwell Hollow, LEM = Lemm Swamp). Star symbol within inset
map of Tennessee indicates the location of AAFB.
Fire Ecology Volume 12, Issue 2, 2016
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Stambaugh et al.: Scale Dependence of Fire Regimes
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using a chainsaw. Cross sections were as-
signed a sample number, orientation, slope di-
rection, and geographic location.
For each study site, re scar history re-
cords consisted of 30 to 50 trees, >100 re
scars, and spanned 250 years or more. Fire
scars on post oaks were dated using standard
dendrochronological techniques (Stokes and
Smiley 1968) utilizing master ring-width
chronologies developed at the study areas
(NOAA 2008; M. Stambaugh, University of
Missouri, Columbia, Missouri, USA, unpub-
lished data). Fire scars were dated to the year
of cambial response to injury and, if during the
growing season, to a within-ring location fol-
lowing methods described by Kaye and Swet-
nam (1999). Fire scars were identied by the
presence of charcoal, callus tissue, and bark
ssure scar patterns (Guyette and Stambaugh
2004). Composite re scar chronologies were
constructed by compiling re scar data for in-
dividual study sites.
Data Analyses
Summary statistics for re scars and inter-
vals were calculated using FHAES and FHX
software (Grissino-Mayer 2001). Fire inter-
vals were dened as the number of years be-
tween two consecutive re events. Mean re
intervals (MFIs) represented the average re
interval length in years. Median re intervals
(i.e., median intervals) were reported when the
distribution of re intervals t the Weibull dis-
tribution. For AAFB, summary statistics were
derived for four time periods associated with
cultural changes: pre-EAS (pre-1834), Eu-
ro-American settlement (1834 to 1926), mili-
tary ownership (post-1926), and the full period
of record. The pre-EAS period at AAFB was
dened as pre-1834 based on the timing of the
Removal Act of 1830, when Native Americans
were forced westward from the region (i.e.,
area containing study sites) with many groups
ultimately residing in Oklahoma. Summary
statistics of re scar data at the WMWR are
published in Stambaugh et al. (2014a) and re-
produced here. At WMWR, time periods were
dened as: pre-EAS (i.e., pre-Fort Sill, 1850),
conict (with Native Americans) and Eu-
ro-American settlement (1850 to 1901), public
ownership (post-1901), and the full period of
record (Stambaugh et al. 2014a).
For individual study sites (n = 8), re in-
tervals were derived from the composite re
scar chronologies (i.e., record of res at the
site based on all scars on all trees) and repre-
sented the occurrence of re somewhere in the
study site. We calculated summary statistics
for re intervals, percentages of trees scarred,
and re scar seasonality. Percentages of trees
scarred were calculated by year then averaged
across all years to generate a mean per site.
Statistics were calculated separately for the
different time periods of interest. For cases in
which re intervals spanned more than one pe-
riod, intervals were assigned to the period with
the majority of the interval years. Percentages
of trees scarred were calculated for years in
which at least four trees were represented in
the record.
To describe the relationship between spa-
tial scale of observation and MFIs, we com-
piled pre-EAS re intervals at three spatial
scales: individual trees (~1 m2, n = 194 re in-
tervals), study sites (~1 km2, n = 152 re inter-
vals), and landscapes (~100 km2, n = 93 re
intervals). We calculated MFIs at the tree, site,
and landscape scale for data from AAFB and
WMWR separately. In addition, we calculated
MFIs across these scales for all data compiled
across both oak woodland study regions.
Ranges and frequency distributions were plot-
ted at each of these scales. Based on the work
of Falk et al. (2007) that demonstrated re fre-
quency followed power-law behavior over
space, we chose to represent the relationship
between MFI and spatial scale with a nega-
tive-exponential model t using SigmaPlot
v12.3 software (SYSTAT Software, San Jose,
California, USA). The presentation of the
model is simply to demonstrate the relation-
Fire Ecology Volume 12, Issue 2, 2016
doi: 10.4996/reecology.1202065
Stambaugh et al.: Scale Dependence of Fire Regimes
Page 71
ship between MFI and spatial scale, not to pro-
vide prediction, since only three spatial scales
were considered.
RESULTS
Fire History at AAFB,
The Barrens, Tennessee
A total of 143 trees were sampled across
the four re history sites at AAFB (Table 2,
Figure 3). The maximum and minimum time
period spanned by sites was 1631 to 2004 (374
yr) and 1727 to 2004 (278 yr), respectively. A
total of 423 re scars and 205 re intervals
were identied from the four study sites (Table
2). When site data were pooled (i.e., land-
scape scale), 138 re intervals were identied.
All sites spanned a common period of 1727 to
2003. When sites were considered separately,
composite re intervals ranged from 1 yr to 35
yr, but when considering the entire landscape,
composite re intervals ranged from 1 yr to 26
yr. For the full period of record for each site,
MFIs ranged from 2.9 yr to 6.5 yr. At decadal
scales, sites shared some similar patterns in
re frequency through time including in-
creased re events in the few decades prior to
1800, decreased re from about 1830 to 1850,
and decreased re in the latter half of the twen-
tieth century (Figure 3). The MFIs among
sites ranged from 3.3 yr to 5.2 yr pre-1834, to
2.5 yr to 10.3 yr from 1824 to 1926, to 5.7 yr
to 10.3 yr post-1926. The trend of longer site
MFIs during the pre-EAS period, to shortened
MFIs following EAS, to longer MFIs in the
latter twentieth century was shared by sites at
both AAFB and WMWR (Tables 1 and 2).
Annual burning (i.e., two re years in se-
quence) occurred at all sites; however, at
Lemm Swamp, this only occurred once while
all other sites had at minimum 10 cases. The
longest re-free period occurred at HCK site
from 1936 to 2003, a 67 yr period (Table 2,
Figure 3).
Low severity res (dened as ≤10 % trees
scarred in a re event) were the most common
across all sites. Overall, percentages of trees
scarred at sites ranged from 2 % to 60 %, the
same range as at WMWR (Table 3). Also sim-
ilar between the landscapes, the percentages of
trees scarred at each site trended downward
between pre-EAS and settlement periods, but
generally trended upward from settlement to
current day (Tables 1 and 2, Figure 3). Based
on tree ages, no evidence of complete stand-re-
placing res occurred at any sites within
AAFB or the WMWR during the period of re-
cord. Fire seasonality was dominated by dor-
mant season res. Both HCK and RCH sites
had exclusively dormant season res. Grow-
ing season scars constituted 3 % at both the
SLT and LEM sites.
Contrasting Fire Regimes between
Tennessee and Oklahoma
Many similarities existed between the his-
torical re regimes in Tennessee and Oklaho-
ma (Tables 1 and 2, Figure 4). Sites spanned
similar time periods, likely due to presence of
post oak reaching maximum longevity. At
sites in both landscapes, re events during the
pre-EAS period were generally less frequent,
with slightly higher average percentages of
trees scarred compared to the following Eu-
ro-American settlement period. For the full
period of record, res were more frequent at
sites (1 km2) in Tennessee than in Oklahoma,
but at the landscape scale (100 km2), they were
similar (MFI = 2.2 years at AAFB versus 2.6
years at WMWR). Both landscapes had pri-
marily dormant season res with slightly
greater numbers of growing season res in
Oklahoma (although seasonality was undeter-
minable for many scars). Ranges of percent-
ages of trees scarred were widest in the pre-
EAS period for both landscapes (Tables 1 and
2). Similarly, mean percentages of trees
scarred decreased in the settlement era when
overall burning frequency increased among
sites.
Fire Ecology Volume 12, Issue 2, 2016
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Stambaugh et al.: Scale Dependence of Fire Regimes
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a based on percentages of sites scarred.
Huckleberry
Ridge
Rowland Creek
Headwaters Saltwell Hollow Lemm Swamp All sites
Spatial extent (km2) ~1 ~1 ~1 ~1 ~100
All years
Time period 1721 to 2003 1727 to 2003 1631 to 2004 1701 to 2004 1631 to 2004
Trees (n) 34 44 35 30 143
Fire intervals (n) 58 58 54 35 138
Mean re interval (yr) 2.9 4.52 5.7 6.5 2.23
Fire interval range (yr) 1 to 13 1 to 35 1 to 28 1 to 32 1 to 26
Median interval (yr) 2.4 3.2 3.9 5.2 na
Mean trees scarred (%) 9.4 8.9 16.1 11.6 38.4 a
Range trees scarred (%) 3 to 39 2 to 40 3 to 60 3 to 38 25 to 100 a
Fire scars (n)112 135 117 59 423
Dormant season res (%) 100 100 96 98 98
Growing season res (%) 00422
Undetermined (%) 0 0 0 0 0
Prior to Euro-American settlement period (before 1834)
Time period 1721 to 1834 1727 to 1834 1631 to 1834 1701 to 1834 1631 to 1834
Trees (n) 22 25 18 17 82
Fire intervals (n) 20 24 31 22 60
Mean re interval (yr) 3.3 3.92 4.45 5.18 2.33
Fire interval range (yr) 1 to 10 1 to 35 1 to 28 1 to 16 1 to 24
Median interval (yr) 2.93 2.48 3.1 4.29 1.64
Mean trees scarred (%) 13.6 10.3 21.3 14.9 43.3 a
Range trees scarred (%) 5 to 29 4 to 30 6 to 60 6 to 38 25 to 100 a
Fire scars (n) 33 38 62 36 169
Dormant season res (%) 100 100 97 97 97
Growing season res (%) 00333
Undetermined (%) 0 0 0 0 0
Euro-American settlement period (1834 to 1926)
Time period 1834 to 1926 1834 to 1926 1834 to 1926 1834 to 1926 1834 to 1926
Trees (n) 33 36 26 30 125
Fire intervals (n) 36 25 10 8 60
Mean re interval (yr) 2.53 3.24 8.4 10.25 1.52
Fire interval range (yr) 1 to 13 1 to 8 2 to 23 3 to 32 1 to 4
Median interval (yr) 1.95 na na na 1.43
Mean trees scarred (%) 7.28 6.07 9.45 7.44 34.17 a
Range trees scarred (%) 3 to 39 3 to 23 4 to 19 3 to 12 25 to 75 a
Fire scars (n) 74 53 23 17 167
Dormant season res (%) 99 100 100 100 100
Growing season res (%) 10000
Undetermined (%) 0 0 0 0 0
Military use (1926 to 2004)
Time period 1926 to 2003 1926 to 2003 1926 to 2004 1926 to 2004 1926 to 2004
Trees (n) 34 44 34 30 142
Fire intervals (n) 1 7 11 3 17
Mean re interval (yr) na 10.29 6.55 5.67 4.35
Fire interval range (yr) na 2 to 32 1 to 26 1 to 11 1 to 26
Median interval (yr) na na 4.25 na 2.7
Mean trees scarred (%) 7.5 14.71 8.5 5 36.11a
Range trees scarred (%) 6 to 9 2 to 40 3 to 18 3 to 7 25 to 75a
Fire scars (n) 5 44 32 6 87
Dormant season res (%) 100 100 91 100 92
Growing season res (%) 00908
Undetermined (%) 0 0 0 0 0
Table 2. Fire scar history data at the site and landscape scale for Arnold Air Force Base. Data are strati-
ed by time periods associated with cultural changes. Data for re intervals on individual trees are not
shown in this table but can be viewed in Figures 3 and 5.
Fire Ecology Volume 12, Issue 2, 2016
doi: 10.4996/reecology.1202065
Stambaugh et al.: Scale Dependence of Fire Regimes
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Figures 3a and 3b. Post oak re scar history charts of two of the four individual study sites at Arnold Air
Force Base in The Barrens region of Tennessee, USA. On study site charts, top boxes indicate numbers of
trees recording (blue line) and percentages of trees scarred (vertical bars) through time. Below, horizontal
lines represent the periods of tree-ring record for individual trees. Bold vertical ticks on horizontal lines
indicate re scar years. On the left ends of lines, vertical ends indicate pith years while diagonal ends indi-
cate inner ring year (rings missing to center). On the right ends of lines, vertical ends indicate bark years
while diagonal ends indicate outer ring years (rings missing to bark). A composite of all re years at the
site is given at the bottom of charts.
a) Huckleberry Ridge
b) Rowland Creek Headwaters
Fire Ecology Volume 12, Issue 2, 2016
doi: 10.4996/reecology.1202065
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Figures 3c and 3d. Post oak re scar history charts of two of the four individual study sites at Arnold Air
Force Base in The Barrens region of Tennessee, USA. On study site charts, top boxes indicate numbers of
trees recording (blue line) and percentages of trees scarred (vertical bars) through time. Below, horizontal
lines represent the periods of tree-ring record for individual trees. Bold vertical ticks on horizontal lines
indicate re scar years. On the left ends of lines, vertical ends indicate pith years while diagonal ends indi-
cate inner ring year (rings missing to center). On the right ends of lines, vertical ends indicate bark years
while diagonal ends indicate outer ring years (rings missing to bark). A composite of all re years at the
site is given at the bottom of charts.
c) Saltwell Hollow
d) Lemm Swamp
Fire Ecology Volume 12, Issue 2, 2016
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Hollis Canyon French Lake
Rain Gauge
Flat Cache Creek All sites
Spatial extent (km2) ~1 ~1 ~1 ~1 ~100
All years
Time period 1720 to 2010 1712 to 2005 1746 to 2009 1637 to 2010 1637 to 2010
Trees (n) 46 54 46 43 189
Fire intervals (n) 34 59 34 34 112
Mean re interval (yr) 7.94 4.73 7.09 7.82 2.63
Fire interval range (yr) 1 to 27 1 to 19 1 to 26 1 to 66 1 to 12
Median interval (yr) 6.14 3.77 5.53 4.49 na
Mean trees scarred (%) 10.31 5.88 11.77 9.22 37.22 a
Range trees scarred (%) 2 to 29 2 to 36 2 to 60 3 to 50 25 to 100 a
Fire scars (n) 105 122 102 91 420
Dormant season res (%) 88 78 80 97 86
Growing season res (%) 02623
Undetermined (%) 12 20 14 1 12
Prior to Euro-American settlement period (before 1850)
Time period 1727 to 1850 1712 to 1850 1746 to 1850 1637 to 1850 1637 to 1850
Trees (n) 31 38 33 31 133
Fire intervals (n) 12 20 13 11 42
Mean re interval (yr) 8.83 6.25 6.46 12.27 3.21
Fire interval range (yr) 2 to 25 1 to 19 1 to 17 3 to 53 1 to 10
Median interval (yr) 6.7 5.53 5.42 9.45 2.87
Mean trees scarred (%) 11.7 9.2 19.64 12.56 36.43 a
Range trees scarred (%) 3 to 29 3 to 36 3 to 60 3 to 33 25 to 100 a
Fire scars (n) 24 49 53 29 155
Dormant season res (%) 92 69 81 100 86
Growing season res (%) 02001
Undetermined (%) 8 29 19 0 14
Conict and settlement period (1850 to 1901)
Time period 1850 to 1901 1850 to 1901 1850 to 1901 1850 to 1901 1850 to 1901
Trees (n) 46 53 34 36 169
Fire intervals (n)11 19 13 18 38
Mean re interval (yr) 3.55 2.42 3.23 2.72 1.29
Fire interval range (yr) 1 to 8 1 to 7 1 to 8 1 to 7 1 to 3
Median interval (yr) 3.35 na 2.99 2.42 na
Mean trees scarred (%) 8.58 4.65 5.23 7.26 41.67 a
Range trees scarred (%) 3 to 19 2 to 10 3 to 12 3 to 32 25 to 100 a
Fire scars (n) 33 38 26 45 142
Dormant season res (%) 85 84 77 93 85
Growing season res (%) 0 3 15 4 6
Undetermined (%) 15 13 8 2 10
Public ownership (1901 to 2010)
Time period 1901 to 2010 1901 to 2005 1901 to 2009 1901 to 2010 1901 to 2010
Trees (n) 46 54 46 43 189
Fire intervals (n) 9 18 6 4 31
Mean re interval (yr) 10.67 5.22 16.67 19.25 3.42
Fire interval range (yr) 1 to 27 1 to 19 7 to 26 2 to 66 1 to 12
Median interval (yr) 8.85 4.04 16.33 8.70 2.89
Mean trees scarred (%) 11 3.68 9 10.4 32.28a
Range trees scarred (%) 2 to 11 2 to 10 2 to 23 3 to 17 25 to 75a
Fire scars (n) 52 35 23 20 130
Dormant season res (%) 88 83 83 95 87
Growing season res (%) 03954
Undetermined (%) 12 14 9 0 9
a based on percentages of sites scarred.
Table 3. Fire scar history data at the site and landscape scale for the Wichita Mountains. Data are strati-
ed by time periods associated with cultural changes. Data for re intervals on individual trees are not
shown in this table, but can be viewed in Figure 5 or Stambaugh et al. 2014a.
Fire Ecology Volume 12, Issue 2, 2016
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Spatial Scale Dependence of Pre-EAS MFIs
Pre-EAS re intervals decreased from the
spatial extent of individual trees (1 m2), to
sites (1 km2), to landscapes (100 km2) (Figure
5). Fire intervals on individual trees ranged
from 1 yr to 38 yr at AAFB, and 1 yr to 90 yr
at WMWR. Mean re intervals on individual
trees were 8.7 yr at AAFB and 19.8 yr at
WMWR. At the site scale, re intervals
ranged from 1 yr to 35 yr (mean = 4.3) at
AAFB, and 1 yr to 53 yr (mean = 8.0) at
WMWR. At the landscape scale, re intervals
ranged from 1 yr to 24 yr (mean = 2.3) at
Figure 4. Fire scar history diagrams for Arnold Air Force Base and Wichita Mountains post oak wood-
land landscapes (areas of approximately 100 km2). Top boxes indicate number of sites recording (blue
line) and percentages of sites scarred (vertical bars) through time. Below, horizontal lines represent the
periods of record of each site (i.e., each horizontal line represents all trees combined from sites shown in
Figure 3). Fire scar dates at the bottom of this chart represent the occurrence of re events within the
landscape extent (~100 km2).
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Figure 5. Pre-EAS period re intervals at the scales of individual tree, site, and landscape. Fire intervals
are separated by site indicated by triangle and circle symbols (see graph at top left for full range of ob-
served intervals). Horizontal bars represent the frequency of observations for each interval. Curves depict
the negative exponential relationship between mean re interval (MFI) and scale. The MFIs at each spa-
tial scale were t with a negative exponential curve. Separate curve ts are shown for data from all oak
woodland sites and the two study landscapes separately.
Fire Ecology Volume 12, Issue 2, 2016
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AAFB, and 1 yr to 10 yr (mean = 3.2) at
WMWR. The negative exponential equation
relating pre-EAS period mean re interval to
spatial extent was given as:
MFI = 12.96 × e(−0.82×area), (1)
where MFI = mean re interval at the respec-
tive spatial extent, area is in km2 (Figure 5).
DISCUSSION
Fire scars on trees are spatially explicit
data, which can be an advantage over other
historical sources such as documentary re-
cords. For example, personal observations
like Swallow’s (1859) commonly cited de-
scription of annually occurring res in Mis-
souri oak woodlands rarely include a spatial
reference. Based on our results, annually oc-
curring res were limited (maximum of 10
times over a three-century period at the study
site extent) and would not be the MFI of post
oak woodlands, unless considering landscape
re occurrence rates for areas >3 km2 (based
on Equation 1 and on re data from four sites
per landscape). Other evidence, such as ex-
perimental burn studies, also suggests that
long-term frequent (<2 yr) to annual burning is
too frequent to sustain tree recruitment in oak
forest communities (Peterson and Reich 2001,
Knapp et al. 2015). One explanation for how
res could have been reported to have histori-
cally burned annually while tree recruitment
was sustained might be due to only portions of
a given landscape burning in a single year
when re occurrence was reported.
Disturbances such as re vary by spatial
and temporal scales due to differences in inu-
ences of drivers and controls (Turner 1987).
Understanding signatures in spatial and tempo-
ral dependence reveals clues to the type and
relative importance of environmental controls.
In the US, networks of historical re scar data
have shown how re regime drivers and con-
trols vary from tree to subcontinental scales,
including their relevance to vegetation change,
human populations and cultures, and climate
conditions (Guyette et al. 2002, 2006; Taylor
and Skinner 2003; Falk et al. 2011). In gener-
al, we found re to be more frequent in Ten-
nessee than in Oklahoma, particularly pre-
EAS. This result is somewhat surprising con-
sidering that Tennessee sites are generally wet-
ter, more humid, and not in a signicantly more
lightning-ignition prone region. Frequent re
regimes, particularly with the aforementioned
conditions, are commonly attributed to anthro-
pogenic inuence (Guyette et al. 2002). Mc-
Clain et al. (2010) found more frequent res
during a pre-EAS period in a post oak wood-
land in Illinois, USA (MFI = 1.97 yr from 1776
to 1850), while Guyette et al. (2003) found less
frequent res in a southern Indiana, USA,
woodland (MFI = 23 yr from 1620 to 1820).
Other studies exist from post oak woodlands in
Oklahoma and Texas, USA, and these report
pre-EAS MFIs between 3.3 yr to 6.7 yr (Clark
et al. 2007, DeSantis et al. 2010, Allen and
Palmer 2011, Stambaugh et al. 2011)values
that fall within the range of data presented
here. All of the post oak re data mentioned
above were derived from sites within the west-
ern and north-central portion of the range of
post oak and, therefore, may not characterize
conditions farther east and south with wetter
and warmer climates, varied vegetation and fu-
els, and differing re regime characteristics
(i.e., re seasonality, ignition sources).
Scale dependence of historical re regimes
could inuence re management planning, the
interpretation of natural and documentary ar-
chival data, and models that simulate landscape
re disturbance (e.g., LANDIS; Wang et al.
2014). In this study, re scar data were used to
explore the scale dependence of re intervals
from tree to landscape scales. Results describ-
ing how re intervals vary by extent are among
the rst reported in the eastern US; additional
studies are needed to test these ndings. Fire
scar wounding measurements paired with re
behavior and burn area information would like-
Fire Ecology Volume 12, Issue 2, 2016
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Stambaugh et al.: Scale Dependence of Fire Regimes
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ly improve relationships and interpretation at
each extent. One expected bias of our re scar
data is that the frequency of re recorded at the
individual tree scale was probably lower than
actually occurred due the fact that individual
trees may not record all re events. In this
case, the characterization of mean re interval
at the individual tree extent could be more fre-
quent than our model (Equation 1) would sug-
gest. Additional biases may affect our results,
such as our inability to randomly select study
site locations within landscapes.
Relevance to Oak Woodland Ecology
and Management
Fire history data provide perspective, and
possibly a basis, for oak forest community
management in the eastern US. The value of
re history data is not only that they inform
management, but also that they further under-
standing of scale effects, landscape re het-
erogeneity, and long-term vegetation dynam-
ics of active re regimes. These data can span
more than 300 years and identify processes
that vary on time scales much longer than pro-
fessionals’ careers or experiments. This is
particularly relevant to open oak canopy struc-
tures such as woodlands and savannas, within
which re disturbance may have been the
most important factor responsible for their ex-
istence and conditions (Dey and Kabrick
2015), but for which little guidance exists
within written documentation, living memory,
or management experience.
For present day management of re-depen-
dent communities, it is important to remember
that, historically, forest community structures
and compositions encountered during EAS
most likely did not previously undergo exten-
sive cutting treatments, despite being the most
common vegetation manipulation technique in
restoration projects today. Further, historical
re conditions (i.e., severity, extent) were not
bound by modern-day societal and physical
barriers (e.g., safety, emissions, roads, chang-
ing land uses), likely allowing for a greater po-
tential for more extensive, longer duration, and
higher severity res to occur historically.
Generally, in eastern hardwood forests, the ef-
fects of cutting vegetation are not a surrogate
for re, particularly in regard to the ground-be-
lowground impacts and thermal selection for
smaller-sized, thin bark vegetation following
low severity res (Waldrop et al. 2008). In-
deed, cutting treatments may be a necessary
activity in woodland and savanna restoration
to achieve the desired structure of trees due to
the limited ability of low intensity res to re-
duce the density of larger diameter trees (e.g.,
trees >10 cm dbh), almost regardless of spe-
cies (Arthur et al. 2015). Bark thickness on
larger diameter trees can be sufcient to pro-
tect the cambium from re-girdling during low
intensity res even for what are considered
re-sensitive species (Hutchinson et al. 2005).
Mechanical thinning of the overstory, in con-
junction with prescribed burning, is commonly
combined in initial restoration efforts until de-
sired structure is achieved that can then be
more easily maintained by a regime of pre-
scribed burning (e.g., Hutchinson et al. 2005,
Waldrop et al. 2008, Kinkead et al. 2013).
It is important to consider the spatial and
temporal variation in historical re regimes
and how those resulted in the mosaic of prai-
rie, savanna, woodland, and forest as re inter-
acted with topography and other site factors
that inuenced ignition potential and re be-
havior. Heterogeneity in re coverage and ef-
fects probably affected historical woodland
conditions (i.e., presence or absence, tree den-
sity, and species). Prescribed re to restore
woodlands is commonly applied to hundreds
to thousands of hectares at a time. Our results
suggest that, within the extent of a landscape,
great variability exists in re frequency. Rec-
ognition and quantication of these distur-
bance properties could aid in understanding
the ecology and management of re-dependent
natural communities. Within safety, social ac-
ceptance, and human resource limitations, re
Fire Ecology Volume 12, Issue 2, 2016
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For work at AAFB, we thank G. Call and C. Strohmeier of ACS Conservation for their sup-
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