Rapid and accurate estimates of microcharcoal content in pollen ...

Rapid and accurate estimates of microcharcoal content in pollen slides
W. Finsinger 1 , 2 , W.Tinner 3 , 4 , F.S. Hu 3
1
Palaeoecology, Laboratory of Palaeobotany & Palynology, Utrecht University, Budapestlaan 4, 3584 CD Utrecht, The Netherlands .
2
Dipartimento di Biologia Vegetale, Università ‘La Sapienza’, P.le A. Moro 5, 00185 Rome, Italy
E-mail: w.finsinger@bio.uu.nl
3
Department of Plant Biology, University of Illinois at Urbana-Champaign, 265 Morrill Hall, 505 South Goodwin Ave, Urbana, IL 61801, USA
4
Institute of Plant Sciences, University of Bern, Altenbergrain 21, CH-3013 Bern, Switzerland
Abstract
Microcharcoal records of sedimentary archives are helpful to estimate the impacts of past forest fires on vegetation, but may also be
used to reconstruct the impact of carbon dioxide released by forest fires on global atmospheric CO 2
concentration. We suggest that if microcharcoal
concentration of sediment samples is estimated using pollen slides, then it would be sufficient to count the particles instead
of measuring their area with sophisticated techniques and obtained minimum count sums to guarantee a good degree of accuracy.
Introduction
Sedimentary charcoal records are widely used to reconstruct
the effects on terrestrial and aquatic ecosystems
of past natural forest-fire occurrence (e.g. Wright 1976;
Whitlock and Larsen 2001; Finsinger et al. 2006) as well
as of anthropogenic deforestation by biomass burning (e.g.
Iversen 1941; Odgaard 1992; Tinner et al. 1999). Charcoal
records can also be used to assess the impact of carbon
dioxide released by forest fires on global atmospheric
CO 2
concentration (e.g. Carcaillet et al. 2002). These topics
are of increasing interest because of the interactions
among climate change, land-use change, biomass burning,
and atmospheric emissions (Fearnside 2000; Kasischke
and Penner 2004). Fire is important in the carbon budget
of some ecosystems (e.g., boreal forests, grasslands, tropical
savannas and woodlands) and is affected directly by
management and indirectly by land-use change (Apps et
al. 1993). Fire is a major short-term source of atmospheric
carbon, but is also a small longer-term sink through production
of slowly decomposing and inert black carbon
(IPCC 2001).
A recent study conducted by Schröter et al. (2005) concluded
that among all European regions, the Mediterranean
appeared most vulnerable to global climate change. Multiple
potential impacts were projected, related primarily to
increased temperatures and reduced precipitation. The impacts
included water shortages and increased risk of forest
fires. It is therefore important to assess (i) how forest fires
altered vegetation and (ii) to what extent forest fires have
contributed to the atmospheric carbon dioxide budget.
Regional (or even global) trends in forest-fire activity can
be revealed by sedimentary charcoal records if a number
of requirements are met:
• Records have similar spatial and temporal resolution,
• Differences in charcoal production between different
vegetation types are negligible,
• Accuracy and reliability of sedimentary charcoal-concentration
estimates are comparable among records.
At present, various preparation methods are used to estimate
charcoal abundance in sediments (e.g., pollen-slides,
thin-sections, sieving, combustion/digestion), resulting
in different spatial and temporal resolutions of this proxy
(e.g. MacDonald et al. 1991; Carcaillet et al. 2001).
Nevertheless, visual analysis of charcoal content in pollen
slides is one of the most commonly used methods, partially
because of the prevalence of pollen analysis in palaeoecological
studies.
In this paper we therefore discuss the extent to which these
requirements are met and the implications for the interpretation
of sedimentary charcoal records from pollen slides.
Spatial resolution
Comparisons of recent fire activity deduced from fire
scars or written historical sources with charcoal records
from lake sediments show that pollen-slide microscopic
charcoal represents regional source areas (MacDonald
et al. 1991; Tinner et al. 1998). These empirical results
confirmed previous theoretical modelling and empirical
results of charcoal-particle transport (Clark 1988; Lynch
et al. 2004), which identified the size of single charcoal
particles as a major factor determining the transport distance.
Larger particles usually derive from a local source
(i.e. within the catchment) while smaller ones are transported
over longer distances (e.g. Patterson et al. 1987).
These assumptions led many charcoal analysts to reconstruct
regional fire regimes by estimating the charcoal area
of particles in pollen slides through visual inspection (e.g.
g. fiorentino, d. magri (eds). Charcoals From The Past, BAR Int. Ser., 2008.

W. Finsinger, W.Tinner, F.S. Hu
Waddington 1969; Swain 1973; Clark 1982) or with
computer-aided techniques (image analysis).
The question whether it is really necessary to measure or
estimate microcharcoal areas has been addressed recently
by Tinner and Hu (2003), who analysed the relationship
between particle-number and particle-area concentration
at three different sites in different biomes. Their comparison
showed that area concentration (mm 2 cm -3 ) and
number concentration (number of charcoal particles cm -3 )
of charcoal particles in pollen slides are strongly correlated
at all three studied sites (Fig. 1). They further established
regression equations for each of the three sites and
assessed to what degree the area concentration at one site
could be predicted using either regression (Fig. 1). Results
indicated that as long as the same pollen-preparation technique
%):(!$%!%%
is used, the equation from one site can be used to
predict
))2%)%$$
area concentration at other sites even if different
vegetation types occur.
$()*)$)(%;3?3
Hence, it is unnecessary to measure or estimate microscopic
charcoal areas in standard pollen-slides (Tinner et
( )$) % % 0 */
al.
**$%:(()%:(!0
1998; Tinner and Hu 2003). The authors, however,
warned
$()*)$$$%
that the high number-area correlation is partially
&!)!!& *$$(3
Difference between vegetation types
If the relationships between charcoal area concentration
and number concentration are similar among sites of vegetation
types, then tedious calibration analyses would be
not strictly necessary at all sites. Tinner and Hu (2003)
further suggested that differences in charcoal size and
size-class distribution among sites mainly reflected different
preparation techniques of pollen samples. These
authors concluded that differences in vegetation type or
other factors (e.g., changes in fire regime related to different
climatic conditions) are unimportant and attributed
the similarities in size and size-class distribution to some
(yet unknown) reason related to specific pollen-preparation
steps. $0$ They suggested $)? that removal (0* of large charcoal )
)!!
() particles through % 0 sieving and decanting F is ) almost F/$ certainly
)( a contributing factor, 0 though ; (>2? not the only. However, ) if the
*$!$ goal is not */** the reconstruction *3 of regional % () fire history % (e.g.
0&!$%$*$%(%&)
by using the pollen-slide technique), differences of vegetation
types may be of interest.
)$0$ $(!$%(%
For instance, including
all
charcoal-size
% 3 2&
fractions released
! %
during
fire
may
be
%
important
for deriving global estimates
$($!!% ;33
of biomass
(%
burning.
*/) $%:(? )!!$! & *
Achieving this goal is challenging at present because it is
0 !3$$()$%$/
difficult to (i) estimate the combustion completeness or
F!$))(!0 0*!
fraction of biomass consumed during fires as a function of
)&0!0(3$%&
%$%*$()!!$(
fuel type and moisture, and (ii) measure emission factors
;?0%$0($0*!$!
for various trace gases and particulate matter for different
0$(0))(!!($!!( vegetation types and fuel moisture content (see for example
discussion 0( in ) Kasischke, ;? 0( Penner 0 2004). !$ !
*
)
&($)*$(0!)!!
& Accuracy and * reliability ) !( 0( of sedimentary $ charcoalconcentration
estimates between
; !
50*)$(A$%>)"77?3
samples
,#+%(%+'-+ %.
-()-%
Charcoal analysts using the pollen-slide technique have to
-%$ decide about the (%*/)$%:(%&
minimum counting sum needed to produce
accurate ( % results 00(0 in pollen-slides. $( (0 Different )) authors
)$)
*)($ have made $$( different ( choices: for */)3 instance, Carcaillet .!! et al.
(% (2001) as %& well 0) as Carrión )!! et al. $%$1 (2003) scanned ! $ the total
-$ surface of - each ;77?2-J pollen-slide, while Odgaard - (1992) ;77? analysed
for % each sample (!$ at least ! one $% entire */) slide, or, 2% in case
$)
@));88? of abundant charcoal-particles, )!$%0*
half a slide. In contrast,
)$!()$%$/*$
Tinner, Conedera (1995) chose a minimum counting sum
%! of at least )3 200 charcoal-particles $ ) for each -) sample, ;88+? while
$%00(0$((0!77$%$/
others (e.g. MacDonald et al. 1991; Sarmaja-Korjonen
*$!$%0*2%%;33D$.)
1998; Tinner et al. 1999; Tinner et al. 2000; Darbyshire
388=0B/AB88,=3888=
3 1 -%$ $$ ;0() 0 ? et al. 2003) measured or counted at least 100 individual
$0*) (0 $$) *)$) $$ 3777=. charcoal fragments. On the %377?0()
other hand some authors do not
(%)2)!!;)2!0Tinner $()77)&)($%$!03@
reveal the counting sum they used for charcoal analysis.
and Hu, 2003?
%%%)0(%)&%$(
This issue has been recently addressed by Finsinger
(0% and Tinner ()!$%$ (2005). Given the 3 assumption of homogeneous
distribution of particles ))) on pollen slides, ) the inferred
$ ($ 0( 0 %(%$
because 0$$*$ large $%$ particles (which tend )) to dominate */) the total
area ;388,=)(77?3%(%
concentration) were eliminated during pollen processing
%2&2)%%%%(0/$
and because small particles (

Rapid and accurate estimates of microcharcoal content in pollen slides
Excel (© Microsoft Corporation; Fig. 2).
Below 200 items (i.e., the sum of charcoal particles and
exotic marker grains), reconstructed number concentration
is either too high or too low. Statistical comparisons show
that the means of bootstrap simulations stabilize after 200
counts. A count of 200-300 items is sufficient to produce a
charcoal-concentration estimate with less than ±5% error
if compared with high-count samples of 1000 items for
charcoal/marker grain ratios p>0.1, p P33 The 8,,3 Holocene, "$13, 0 537-546. ) % ! $%$ 1
77 **)%$!)03"*+/
regrowth in northern Ethiopia during the last 3000 years.
0>))32&%$((0!77 ++3
$%$!00 %%0$3
techniques may be more promising (e.g. Thevenon et al., ($*)*)0*3R( Ef r o n, B., Ti b s h i r a n i, R.J., 1991. Statistical data analysis $% in the
50*2% N73

W. Finsinger, W.Tinner, F.S. Hu
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