Frequent Fires in Ancient Shrub Tundra: Implications of
Paleorecords for Arctic Environmental Change
Philip E. Higuera
1¤a¤b
*, Linda B. Brubaker
1
, Patricia M. Anderson
2
, Thomas A. Brown
3
, Alison T.
Kennedy
4
, Feng Sheng Hu
5,6
1 College of Forest Resources, University of Washington, Seattle, Washington, United States of America, 2 Department of Earth and Space Sciences and Quaternary
Research Center, University of Washington, Seattle, Washington, United States of America, 3 Lawrence Livermore National Laboratory, Center for Accelerator Mass
Spectrometry, Livermore, California, United States of America, 4 Department of Earth Sciences, Montana State University, Bozeman, Montana, United States of America,
5 Department of Plant Biology, University of Illinois, Urbana, Illinois, United States of America, 6 Department of Geology, University of Illinois, Urbana, Illinois, United States
of America
Abstract
Understanding feedbacks between terrestrial and atmospheric systems is vital for predicting the consequences of global
change, particularly in the rapidly changing Arctic. Fire is a key process in this context, but the consequences of altered fire
regimes in tundra ecosystems are rarely considered, largely because tundra fires occur infrequently on the modern
landscape. We present paleoecological data that indicate frequent tundra fires in northcentral Alaska between 14,000 and
10,000 years ago. Charcoal and pollen from lake sediments reveal that ancient birch-dominated shrub tundra burned as
often as modern boreal forests in the region, every 144 years on average (+/2 90 s.d.; n = 44). Although paleoclimate
interpretations and data from modern tundra fires suggest that increased burning was aided by low effective moisture,
vegetation cover clearly played a critical role in facilitating the paleofires by creating an abundance of fine fuels. These
records suggest that greater fire activity will likely accompany temperature-related increases in shrub-dominated tundra
predicted for the 21
st
century and beyond. Increased tundra burning will have broad impacts on physical and biological
systems as well as on land-atmosphere interactions in the Arctic, including the potential to release stored organic carbon to
the atmosphere.
Citation: Higuera PE, Brubaker LB, Anderson PM, Brown TA, Kennedy AT, et al (2008) Frequent Fires in Ancient Shrub Tundra: Implications of Paleorecords for
Arctic Environmental Change. PLoS ONE 3(3): e0001744. doi:10.1371/journal.pone.0001744
Editor: Jerome Chave, Centre National de la Recherche Scientifique, France
Received January 28, 2008; Accepted February 5, 2008; Published March 5, 2008
Copyright:
2008 This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration which stipulates that, once
placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful
purpose.
Funding: Funding was provided by the U.S. National Science Foundation through a Graduate Research Fellowship to PEH and award number 0112586 to LBB,
PMA, and TAB from the Arctic System Science Program.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: philip.higuera@montana.edu
¤a Current address: Montana State University, Department of Earth Sciences, Bozeman, Montana, United States of America
¤b Current address: Department of Plant Biology, University of Illinois, Urbana, Illinois, United States of America
Introduction
Tundra and boreal ecosystems store one third of the world’s soil
carbon [1]. The fate of this vast carbon stock has become a major
concern to global-change scientists because its release to the
atmosphere could exacerbate CO
2
–related climate change [2–6].
Unfortunately, uncertainty about a number of ecosystem processes
hampers predictions of future tundra carbon cycling and the
potential consequences to the climate system. One of the most
important processes is how vegetation and climate change will alter
fire regimes of tundra regions [2,6,7]. Available evidence suggests
that ongoing vegetation and climate change could significantly
increase the rate of burning in northern tundra [8], which is
currently dominated by low-biomass communities (graminoids,
herbs, and dwarf shrubs) that seldom burn [e.g. only 3% of Alaskan
tundra burned between CE 1950 and 2005; Fig. 1; 9]. In particular,
a marked increase in shrub abundance and density, likely resulting
from climate warming [10], is changing the physiognomic structure
of arctic and subarctic regions. Shrubby growth forms increase the
abundance of fine fuels available for burning, and in light of 3–5uC
warming predicted over the next century [8] such fuel changes
could result in fire regimes vastly different from those in modern
tundra. Unfortunately, short observational fire records [e.g. 48 and
57 years in Canada and Alaska; 9,11], a lack of fire-history studies,
and the possibility of novel future vegetation [12] result in little
information to evaluate how tundra fire regimes may respond to
future climate and vegetation change. The paleoecological
approach circumvents these limitations and offers the only way to
obtain long-term empirical records of fire and vegetation change
relevant for understanding tundra fire regimes under future climate
and vegetation scenarios.
Here we present fire and vegetation reconstructions from
northcentral Alaska that document frequent fires in shrub tundra
during the late-glacial and early-Holocene periods (14-10 ka BP
[ka BP = thousand calendar years before present, CE 1950]).
Vegetation and climate controls of these unusual fire regimes are
inferred from paleovegetation records from each of two sites and
from regional paleoclimate interpretations for this period. We also
present an analysis of the climate space occupied by modern
tundra vegetation and modern tundra fires in Alaska (CE 1950–
2004). This analysis provides additional support for the climate-
fire relationships inferred from the paleo-data.
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Results
Trends in charcoal accumulation rates (pieces cm
22
yr
21
,
CHARs) correspond markedly with shifts in pollen assemblages at
Xindi and Ruppert lakes (Fig. 2). Both records start in herb-
dominated tundra (Herb Tundra Zone), indicated by high pollen
percentages of Cyperaceae (sedge), Poaceae (grass), and minor
herb taxa (e.g. Artemisia [wormwood], data not shown). Raw
CHARs are low (medians = 0.01 and 0.00 pieces cm
22
yr
21
) with
few identified peaks in the detrended series (Fig. 2), suggesting little
or no burning in the late-glacial herb tundra near these sites.
Increases in CHARs (medians = 0.05 and 0.02 pieces cm
22
yr
21
)
and the frequency of peaks in the detrended series coincide with a
prominent rise in Betula (birch) pollen percentages (from ,5 to 50–
75%; 14.3 and 13.3 ka BP at Xindi and Ruppert lakes,
respectively), which marks the expansion of Betula shrubs in the
study area (Fig. 2). These pollen assemblages (Shrub Tundra Zone)
have higher Betula percentages than pollen assemblages from
modern tundra in North America [13] (e.g. 70% vs. 40%) and are
thought to represent extensive thickets of tall (.1m) Betula
glandulosa [resin birch, inferred from measurements of pollen
morphology, 14]. The inferred vegetation of the Shrub Tundra
Zone contrasts with the majority of modern circumpolar Arctic
tundra, where only 12% of the area contains shrubs taller than
0.4 m [i.e. Low-shrub tundra; 15]. However, the vegetation
structure of the Shrub Tundra Zone may be analogous to future
Arctic tundra, which is predicted to have a major component of
.0.5-m tall Betula, Salix (willow), and Alnus (alder) shrubs [10,16].
Deciduous woodlands (Deciduous Woodland Zone), identified by
samples with .10–20% Populus (poplar) pollen, characterized the
vegetation from 10.5-9.0 ka BP (Fig. 2). As in the Herb Tundra
Zone, the low raw CHARs (medians = 0.02 and 0.01 pieces cm
22
yr
21
) and few peaks in the detrended series suggest less frequent
fires as compared to the Shrub Tundra Zone.
Estimated fire frequencies within the Shrub Tundra Zone
(Figs. 2, 3) were much higher than in modern tundra [9,11] (Fig. 1).
Fire events (i.e. CHAR peaks) occurred on average (95% CI) every
150 (113–189) years at Xindi Lake and 137 (107–171) years at
Ruppert Lake, with high variability around these means (fire
return intervals [FRIs] range from 30–360 yr; Fig. 3). FRI
distributions at these two sites were statistically indistinguishable
during this period (p = 0.60, n = 24, 20) and from FRI distributions
in the late-Holocene boreal forests around Ruppert, Code, and
Wild Tussock lakes (p ranges from 0.29–0.99, n ranges from 20–
39; see Materials and Methods; Fig. 3; Fig. S1). The fire-vegetation
relationships observed at Ruppert and Xindi lakes during the
Shrub Tundra Zone are likely regional in scale, as this tundra type
is documented in a large network of pollen and macrofossil records
in northcentral Alaska [12,13,17], and high fire activity has been
qualitatively inferred from discontinuous charcoal records at other
sites in interior Alaska [18,19] (Fig. 1B).
Discussion
High fire frequencies in the ancient shrub tundra prompt
questions about the relative roles of vegetation (fuels) and climate
(summer temperature and precipitation) in controlling fire regimes
in the Shrub Tundra Zone and the implications of this natural
experiment for understanding future Arctic environmental change.
Climate is perhaps most often invoked to explain past changes in
fire regimes. However, the influence of climate on the fire regime
in the Shrub Tundra Zone is not straightforward. Near the end of
Betula shrub dominance and afterwards (ca 11.5-9.0 ka BP),
summer temperatures in northern Alaska may have approached or
Figure 1. Distribution of modern circumpolar Arctic tundra [15], Alaskan fires from CE 1950–2005, and sites referred to in the text.
(A) Black rectangles indicate circumpolar regions showing recent increases in shrub densities and/or extent [10]. (B) Alaskan fires from CE 1950–2005
(red polygons) in tundra and boreal forest. Fires burned only 3% percent of Alaskan tundra, representing 6% of the total area burned in the state. Blue
dots identify lakes used in this study: Ruppert (RP) and Xindi (XI) lakes contain records of fire and vegetation from the Shrub Tundra Zone; Ruppert,
Code (CO), and Wild Tussock (WK) lakes contain records from the Boreal Forest Zone (5.5-0 ka BP). Sediment-charcoal records from Sithylemenkat
Lake (1) [19] and Lost Lake (2) [18] also show qualitative evidence of increased fire activity within the Shrub Tundra Zone.
doi:10.1371/journal.pone.0001744.g001
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exceeded modern levels [20]. However, such a temperature rise
cannot explain the increase in fire frequencies at the beginning of
the Shrub Tundra Zone, ca 14.0-12.0 ka BP. In contrast,
paleoclimate proxies [13] suggest that this period was character-
ized by cooler-than-present summers. Furthermore, lowered lake
levels in interior Alaska indicate that effective moisture was lower
than present throughout the Shrub Tundra Zone [21]. Because
summer temperatures were cooler than modern, low effective
moisture must have been a key factor facilitating the fuel drying
necessary to maintain high fire activity within the ancient shrub
tundra. The importance of low effective moisture for facilitating
tundra burning is evident in the pattern of 232 tundra fires that
burned in Alaska between CE 1950–2005. These fires were
significantly skewed to tundra regions with relatively dry and/or
warm summer climate conditions, i.e. with mean June precipita-
tion between 20–30 mm and mean June temperature between 6–
10uC (Fig. 4).
Given our current understanding of late glaciation and the early
Holocene, increased burning in the Shrub Tundra Zone was not a
simple function of climate change. The distinct increase in CHARs
and CHAR peaks at the onset of the Shrub Tundra Zone suggests
that vegetation was a key element facilitating fires. The tall growth
form, small stem diameters, and highly resinous twigs of B.
glandulosa [22] make it susceptible to fire on modern landscapes
[23], and a widespread cover of B. glandulosa in the past would
have created the continuity of flammable fuels necessary for
fire spread. In addition, vigorous sprouting following fires [23]
would have provided the regeneration necessary to sustain fire
Figure 2. Fire and vegetation reconstructions from northcentral Alaska. Chronology, pollen stratigraphy, inferred vegetation, and high-
frequency variations in charcoal accumulation rates (CHARs) from (A) Xindi Lake and (B) Ruppert Lake. Pollen percentage curves are smoothed to
500 years and color coded. CHAR records represent residuals after removing 500-year trends, and red lines around CHAR = 0 are thresholds
identifying noise-related variations. Red plus marks identify CHAR peaks exceeding the positive threshold (and a minimum-count screening; see
Materials and Methods) and are interpreted as local fire events. At both sites CHARs and CHAR peaks increase distinctly with the rise in Betula pollen
percentages, marking the transition from the Herb Tundra Zone to the Shrub Tundra Zone.
doi:10.1371/journal.pone.0001744.g002
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frequencies similar to those of modern boreal forests (Fig. 3). Based
on paleo and modern relationships between tundra fire occurrence
and corresponding climatic conditions, the role of fuels is central to
understanding past and future shifts in tundra fire regimes. In the
case of the Shrub Tundra Zone, the combination of abundant
flammable fuels and low effective moisture overwhelmed the
mitigating effects of low temperatures on landscape flammability.
Overall, paleorecords from northcentral Alaska imply that
ongoing shrub expansion and climate warming will result in
greater burning within northern tundra ecosystems. The geo-
graphic extent of fire-regime changes could be quite large, as
shrubs are expected to expand over the next century in both herb
and low shrub tundra ecosystems, which comprise 67% of
circumpolar Arctic tundra [10,15] (Fig. 1). Over this same period,
annual temperatures in the Arctic are projected to increase
between 3–5uC over land, lengthening the growing season and
likely decreasing effective moisture (in spite of increased summer
precipitation) [8]. How long might it take for the current shrub
expansion to trigger a significant change in fire frequencies?
Within the chronological limitations of our records, past shrub
expansion and fire-regime changes at each site occurred within a
few centuries (Fig. 2). The duration of this shift is consistent with
the estimated rate of shrub expansion within a large area of
northern Alaska [0.4% yr
21
for ca 200,000 km
2
; 10]. Based on a
simple logistic growth model and the assumption of a constant
expansion rate, Tape et al. [10] hypothesize that the ongoing shrub
expansion in this region started roughly 125 years ago and should
reach 100% of the region in another 125 years. Thus, if fuels and
low effective moisture are major limiting factors for tundra fires,
we predict that fire frequencies will increase across modern tundra
over the next several centuries.
Although our fire-history records provide unique insights into
the potential response of modern tundra ecosystems to climate and
vegetation change, they are imperfect analogs for future fire
regimes. First, ongoing vegetation changes differ from those of the
late-glacial period: several shrub taxa (Salix, Alnus, and Betula) are
currently expanding into tundra [10], whereas Betula was the
primary constituent of the ancient shrub tundra. The lower
flammability of Alnus and Salix compared to Betula could make
future shrub tundra less flammable than the ancient shrub tundra.
Second, mechanisms of past and future climate change also differ.
In the late-glacial and early-Holocene periods, Alaskan climate
was responding to shrinking continental ice volumes, sea-level
changes, and amplified seasonality arising from changes in the
seasonal cycle of insolation [13]; in the future, increased
concentrations of atmospheric greenhouse gases are projected to
cause year-round warming in the Arctic, but with a greater
increase in winter months [8]. Finally, we know little about the
potential effects of a variety of biological and physical processes on
climate-vegetation-fire interactions. For example, permafrost
melting as a result of future warming [8] and/or increased
burning [24] could further facilitate fires by promoting shrub
expansion [10], or inhibit fires by increasing soil moisture [24].
Despite these uncertainties, Alaskan paleorecords provide clear
precedence of shrub-dominated tundra sustaining higher fire
frequencies than observed in present-day tundra. The future
expansion of tundra shrubs [10,16] coupled with decreased
effective moisture [8] could thus enhance circumpolar Arctic
burning and initiate feedbacks that are potentially important to the
climate system. Feedbacks between increased tundra burning and
climate are inherently complex [3–5], but studies of modern
tundra fires suggest the possibility for both short- and long-term
impacts from (1) increased summer soil temperatures and moisture
levels from altered surface albedo and roughness [24], and (2) the
release soil carbon through increased permafrost thaw depths and
the consumption of the organic layer [24,25]. Given the
importance of land-atmosphere feedbacks in the Arctic [26–28],
the precedence of a fire-prone tundra biome should motivate
Figure 3. Fire return intervals (FRIs) from the Shrub Tundra
Zone and the conifer-dominated Boreal Forest Zone (5.5-0 ka
BP). FRIs from the Shrub Tundra Zone at (A) Xindi Lake and (B) Ruppert
Lake with fitted Weibull models (blue lines). Weibull (Wbl) b (yr) and c
(unitless) parameters, and the mean FRI (mFRI; yr) all include 95%
confidence intervals. (C) Weibull models from the Shrub Tundra Zone
(blue solid lines) and the Boreal Forest Zone (black dashed lines). All FRI
distributions presented are statistically similar based on likelihood-ratio
tests (p.0.29; see Results). The Weibull b and c parameters, and mFRI
for Ruppert (boreal forest), Code, and Wild Tussock lakes are 188 (147–
239), 150 (123–178), and 149 (123–174); 1.53 (1.31–2.06), 1.85 (1.52–
2.60), and 1.96 (1.61–2.75); 171 (135–216), 135 (113–160), and 135 (113–
157), respectively.
doi:10.1371/journal.pone.0001744.g003
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further research into the controls of tundra fire regimes and links
between tundra burning and the climate system.
Materials and Methods
Lake sediment cores
We reconstructed fire and vegetation history from macroscopic
charcoal and palynological data preserved in sediments from four
lakes in the southcentral Brooks Range (Fig. 1B). Ruppert Lake
(3 ha; N 67u049160, W 154u149450; 230 m asl) and Xindi Lake
(7 ha; N 67u049420, W 152u299300; 240 m asl) have records
spanning late glaciation and the early Holocene (15-9 ka BP). Both
sites are surrounded today by Picea mariana (black spruce)
dominated boreal forest. Additionally, late-Holocene (last 5.5 ka
BP) charcoal records from Ruppert, Code (2 ha; N 67u099290,W
151u519400; 250 m asl), and Wild Tussock (15 ha; N 67u079400,W
151u229550; 290 m asl) lakes provide information about fire
regimes from the modern boreal forest [as defined by 17] for
comparison with late-glacial and early-Holocene records.
Two parallel, overlapping sediment cores were collected from
the center of each lake in summer 2001 (Code,), 2002 (Ruppert),
and 2003 (Xindi, Wild Tussock) using a modified Livingstone-type
piston corer [29] and sliced at 0.25–0.5 cm intervals in the
laboratory. Subsamples of 1 cm
3
were prepared at varying
intervals for pollen analysis according to PALE protocols [30],
and pollen was counted to a terrestrial sum .300 grains at 400–
10006magnification. For charcoal analysis, 3–5 cm
3
subsamples
were taken from contiguous core slices, soaked in sodium
metaphosphate for 72 hours, washed through a 150 mm sieve,
and bleached with 8% H
2
O
2
for 8 hours. Charcoal was identified
at 10–406magnification based on color, morphology, and texture
[31].
Chronologies
Chronologies are based on accelerator mass spectrometry
(AMS)
14
C dates of Betula macrofossils, concentrated Picea pollen
grains, and/or concentrated charcoal particles, and all ages are
expressed as calibrated
14
C years before present (CE 1950; Table
S1). AMS
14
C ages were calibrated using CALIB 5.0 and the
IntCal 04 dataset [32]. Calibrated dates and corresponding
confidence intervals represent the 50
th
, 2.5
th
and 97.5
th
percentiles
of the cumulative probability density function of calibrated ages,
Figure 4. Climate space occupied by Alaskan tundra in the circumpolar Arctic vegetation map [15] and area burned within the same
region from CE 1950–2005. Darker shades represent a greater proportion of total tundra vegetation (gray) or total area burned (red) within the
climate space. Mean June temperature and precipitation distributions associated with tundra vegetation and area burned are shown as histograms
and box plots. For both temperature and precipitation, distributions of vegetation and area burned differ significantly based on a Kolmogorov-
Smirnov test with N
fires
= 232 degrees of freedom (p,0.01). Most fires occurred in areas with a mean June temperature of 6–10uC and a mean June
precipitation of 20–30 mm. The general bias towards warm and/or dry portions of the total climate space suggests an overriding importance of low
effective moisture for facilitating tundra burning.
doi:10.1371/journal.pone.0001744.g004
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respectively [33]. Chronologies were developed using a weighted
cubic smoothing spline with the smoothing parameter determined
by the average distance (cm) between dates, such that greater
sampling resulted in a more flexible spline. The inverse of the 95%
confidence interval of the calibrated
14
C date was used for
weighting.
Given the density of radiocarbon dates in and around the Shrub
Tundra Zone, and that CHARs are sensitive to sedimentation
rates, we evaluated whether general features of the CHAR series at
Xindi and Ruppert lakes varied significantly when using 5–7
alternative age-depth models. In no case did high CHARs or the
distinct peaks of the Shrub Tundra Zone disappear. Charcoal
concentrations (pieces cm
23
) are also high in this period, giving us
confidence that the high CHARs reflect increased charcoal
accumulation and are not chronological artifacts.
Statistical treatment of charcoal data
Peaks in the charcoal accumulation rate (pieces cm
22
yr
21
;
CHAR) in lake sediment records have been shown both
empirically [34] and through mechanistic models [35] to be
associated with the local (0.5–1.0 km) occurrence of individual or
multiple high-severity fires (‘‘fire events’’). Local fires introduce
charcoal to a lake via airborne fallout and create distinct CHAR
peaks that exceed variability around a low-frequency trend. This
characteristic can be taken advantage of to infer when local fires
occurred in the past. We estimated the timing of fire events in our
charcoal records by removing low-frequency trends (i.e. ‘‘back-
ground’’; reflecting changes in the rates of charcoal production,
secondary transport, sediment mixing, and sediment sampling
[31]) and applying a locally-defined threshold value that separates
fire-related CHAR peaks (i.e. signal) from non-fire-related
variability in CHARs (i.e. noise). Our approach accounts for
changes in both the mean and variability of CHARs through time
and the statistical nature of charcoal counts.
Prior to quantitative analysis, charcoal data were interpolated to
constant 15-yr time steps, approximating the median temporal
resolution of each record. Low-frequency trends in CHARs,
C
background
, were modeled with a 500-yr running median, smoothed
with a locally-weighted regression (also with a 500-yr window). We
subtracted C
background
from the interpolated charcoal series to obtain
a residual ‘‘peak’’ series, C
peak
. For each sample in each record, we
identified charcoal peaks when C
peak
exceeded a sample-specific
threshold value. Our threshold criterion assumes that fires create
charcoal peaks that exceed C
peak
variations related to sediment
mixing, sediment sampling, and analytical noise, and that this
variability changes on time scales $500 years. Thus, for each 500-
yr period, we assume that the distribution of C
peak
values contains
two sub-populations: C
noise
and C
fire
. C
noise
is a normally-distributed
population centered near 0 (i.e. C
background
); C
fire
samples are high
CHARs exceeding variations in C
noise
, presumably caused by local
fires. We used a Gaussian mixture model to identify the mean and
variance of the C
noise
distribution [36], and we used the 99
th
percentile of this distribution as the threshold value separating C
fire
from C
noise
. For all records, this procedure was done for each
overlapping 500-yr period, producing a unique threshold for each
sample. Individual thresholds for each sample were smoothed with
a locally-weighted regression (to 500 yr). Finally, all peaks
exceeding the locally-defined threshold were screened based on
the original charcoal counts contributing to each peak. If the
maximum count in a CHAR peak had a .5% chance of coming
from the same Poisson-distributed population as the minimum
charcoal count within the proceeding 75 years, then the ‘‘peak’’
was not identified [e.g. Charster user’s guide, accessed September
2007, http://geography.uoregon.edu/gavin/charster/Analysis.
html; 37]. Our methods are contained within the program
CharAnalysis, written by PEH and freely available at http://
CharAnalysis.googlepages.com.
Quantifying fire regimes
We used dates of estimated fire events to calculate fire return
intervals (years between fire events; FRIs), and we fit a two-
parameter Weibull model to the distribution of FRIs within each
vegetation zone using maximum likelihood techniques [38]. Each
Weibull model passed a Kolmogorov-Smirnov goodness-of-fit
test (p .0.10), and we estimated 95% confidence intervals for the
Weibull scale, b, and shape, c, parameters based on 1000
bootstrapped samples from each population. Confidence intervals
for the mean FRI were calculated in the same manner. We used a
likelihood ratio test, based on likelihood values of the Weibull
models, to test the null hypothesis that any two FRI distributions
were similar [38,39]. The probability of Type I Error, p, was
estimated using a permutation test, and the null hypothesis was
rejected if p,0.05.
Climate space of modern tundra and tundra fires
The climate space occupied by modern tundra vegetation and
tundra fires was quantified using tundra classification data from
the circumpolar Arctic vegetation map [15], temperature and
precipitation data from the Global Historical Climatology
Network [W. Cramer. 2006 University of California-Berkeley,
Integrative Biology and U.S. Geological Survey, Alaska Geo-
graphic Science Office. Accessed on-line in January 2007: http://
agdc.usgs.gov/data/projects/hlct/hlct.html#A], and area
burned ><?show=ts]data from the Alaska Fire Service [accessed
on-line in January 2007: http://agdc.usgs.gov/data/blm/fire/
index.html]. Climate data represent averages across variable
periods, starting from 1888–1968 and generally ending in 1990.
Each dataset was imported into a raster-based geographic
information system with a 1 km
2
cell size. Climate space was
determined based on the average June precipitation and average
June temperature values from all cells with: (1) CAVM
classification of tundra, and (2) burned cells with a CAVM
classification of tundra.
Supporting Information
Table S1 Radiocarbon dates and calibrated ages for Ruppert,
Xindi, Code, and Wild Tussock lakes.
Found at: doi:10.1371/journal.pone.0001744.s001 (0.01 MB
PDF)
Figure S1 High-frequency trends in the charcoal accumulation
rate (CHAR) within the Boreal Forest Zone (5.5 ka BP - present)
at Ruppert, Code, and Wild Tussock lakes. Red lines represent
modeled variations in C
noise
, and plus marks identify peaks
interpreted as local fire events, as in Fig. 2. Inferred fires from
these sites were used to derive the boreal forest Weibull models
presented in Fig. 3. See Materials and Methods for details.
Found at: doi:10.1371/journal.pone.0001744.s002 (1.67 MB TIF)
Acknowledgments
Sampling was conduced under permit from Gates of the Arctic National
Park and the Bureau of Land Management. We thank B. Clegg, J. Mauro,
and K. Shick, for field assistance, Brooks Range Aviation and VECO Polar
Resources for field logistics, C. Adam, E. Cudaback, J. Leach, A. Lilienthal
(Yambor), J. Smith, and E. Spaulding for laboratory assistance, and C.
Whitlock, C. Carcaillet, and two anonymous reviewers for constructive
comments on the manuscript.
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Author Contributions
Conceived and designed the experiments: FH PH LB PA. Performed the
experiments: PH. Analyzed the data: PH AK. Wrote the paper: PH.
Other: Provided significant input to the manuscript: FH. Gathered and
summarized data on modern tundra fires: AK. Oversaw 14C dating and
assisted in chronology development: TB. Counted pollen from Xindi Lake:
PA. Provided significant input to the manuscript: PA LB. Counted pollen
from Ruppert Lake: LB.
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Fires in Ancient Shrub Tundra
PLoS ONE | www.plosone.org 7 2008 | Volume 3 | Issue 3 | e0001744