The effect fire frequency has on the passive carbon pool
by
Morgan L. Wiechmann
An Undergraduate Thesis Proposal
Submitted in Partial Fulfillment for the Requirements of
Bachelor of Arts
in
Geography and Earth Science
Carthage College
Kenosha, Wisconsin
March 2012
Page 1 of 38
The effect fire frequency has on the passive carbon pool
Morgan Wiechmann
______________________________________________________________________________
Abstract
Because of the impact increased amounts of carbon dioxide are having on the
climate, studying the global carbon cycle has generated significant concern and
interest (Jagadamma, 2010; Sollins, 2007; von Luetzow, 2006). Being one of the
largest pools of carbon on the planet, stable soil organic matter (the passive carbon
pool) held underground is important to study because of the potential soil may have
to serve as a carbon reservoir. Never before has the passive pool been studied along
a fire gradient with a long prescribed burn history. The passive carbon pool was
quantified from an oak savanna in central Minnesota. Soil samples were collected
from different annual prescribed burn plots part of an experiment that started in
1964 and fire frequencies ranging from 0.00-0.88 prescribed burn occurrences/
year. Samples were also collected from nitrogenfertilzer (NH4NO3) enriched
experiment gradient plots (0-50 g/m2/ year). Different physical and chemical
fractionation methods were used to separate the passive carbon and the
effectiveness to accurately isolate the pool was also analyzed. The passive carbon
pool increased
slightly with increased fire frequency (p- value= 0.319) and
significantly decreased with increasing nitrogen content (p- value= 6.77E-20). Also,
chemical fractionation with H2O2 oxidation was very effective in removing fast
cycling carbon. The results from this study showed that increase fire frequency
enlarges the size of the passive carbon pool and additional nitrogen in the soil
decreases the passive carbon pool size.
Keywords: carbon; soil organic matter; fire; nitrogen; carbon stabilization
______________________________________________________________________________
Page 2 of 38
Table of Contents
Abstract………………………………………………………………………………….………………………......………...2
List of Figures……………………………………………………………………………........................................4
Introduction……………………………………………………………………………….......................................5
Literature Review…………………………………………………………………............................................7
Recalcitrant/ Passive Soil Carbon Pool………………………………………………………………..7
Stabilizing Methods…………….……………………………………………….……………………………..9
Soil Organic Matter Separation Methods….…………....…………………………………….....13
Study Site…………………………………………………………...…..….................................17
Fire Frequency……………………………...……………………………………................................18
Nitrogen Availability in Soil………………………………………………………………………………..19
Methodology.………………………………………………………………………….…………………………………….20
Soil Sampling…...................…………………………………………………….............................20
Laboratory Processing and Analysis. ……….…………………………………........................24
Results………………………………………………………………………………..............................................26
Discussion……………………………………………………………………………............................................30
Fire Frequncy Effects on the Recalcitrant/ Passive Soil Carbon Pool…………………..30
Nitrogen effects on the Recalcitrant/ Passive Carbon Pool………………………...........31
Methodology……………………………………………………………………………………………………..32
Conclusion……………………………………………………………………………………………………………………...32
Acknowledgements............................................................................................................34
References..........................................................................................................................35
Page 3 of 38
List of Figures
Figure 1: Carbon transformation pathways in soil
9
Figure 2: Changes in mineralization of carbon
11
Figure 3: Carbon residence time with increase clay content
11
Figure 4: Decreased soil nitrogen availability due to fire
13
Figure 5: Black Ccarbon methods continuum
16
Figure 6: Map of study site location
21
Figure 7: Map of burn plots
23
Figure 8: Linear regression of heavy fraction material with increased burn frequency
and nitrogen content
27
Figure 9: Linear regression of final passive carbon pool and fire frequency
28
Figure 10: Linear regression of final passive carbon pool and nitrogen content
29
Figure 11: Histogram of carbon removal when applied to each method
30
Page 4 of 38
Introduction
Recently the global carbon cycle has generated significant concern and interest
(Jagadamma, 2010; Sollins, 2007; von Luetzow, 2006). This is because of the impact
increased amounts of carbon dioxide are having on the global climate. The Kyoto
Protocol on climate change in 1992 desired more research on soil carbon and its
potential to act as a carbon sink and sequester carbon. Being one of the largest pools of
carbon on the planet (second after the oceans), the stable soil organic matter held
underground is important to study because of the potential soil may have to serve as a
carbon reservoir. Therefore, soil can store carbon underground, which will not
contribute to greenhouse gases above ground.
There is still much to learn about stable carbon stored in the soil. The soil carbon
sink may allow large amounts of carbon dioxide (CO2) to be removed from the
atmosphere and sequestered into the soil, creating a negative feedback loop to rising
CO2 in the atmosphere (Sollins, 2007). However, other predictions have suggested a
possibility that rising temperatures and increased flooding may result in increase
respiration rates that will create a positive feedback loop, meaning that temperatures
may rise faster than before (Sollins, 2007). The diverse predictions and uncertainty on
how large amounts of soil organic matter will respond to global climate change make
studying soil carbon worthwhile. Understanding the underlying mechanisms that
stabilized organic matter is essential for predicting CO2 flux between the atmosphere
and soil under a changing climate (Sollins, 2007).
Studying soil carbon is innovative; the uncertainties regarding soil organic carbon
lie in the understanding of the different types of carbon in the soil. One carbon pool
type is fast cycling and quickly exit’s the soil through microbial respiration, known as the
active carbon pool. The other pool of carbon in the soil is the passive carbon pool. The
passive carbon pool is much larger and is considered stabilized carbon because it cannot
easily decompose and remains in the soil for 10-100s of years. A better understanding
Page 5 of 38
of the passive carbon pool is crucial because changes that are occurring in soil organic
carbon may be result of variations in the passive pool (Torn, 1997). The size and long
mean residence time, which is the amount of time carbon exists in the soil, makes
studying the passive carbon pool essential in better understanding of the global carbon
cycle and fundamentally climate change. One major disturbance that could affect the
passive carbon pool is fire.
Changing temperatures are having an effect on forest disturbances such as
wildland fires. Studies have shown that fire severity in the U.S and North America has
increased with warmer and drier conditions (Brown et. al., 2003). The frequency and
intensity of fire ultimately determines its effect on ecosystem processes (Ceterini, 2005).
Soil carbon is one ecosystem process fire may have an effect on. Never before has the
passive carbon pool been studied across a burn gradient with a known long term fire
history. Studying how the passive carbon pool will react to fire will help determine soil
carbon stabilization when fire occurs.
For this project, a long- term prescribed burning experiment in a Minnesota oak
savanna was utilized to determine the role fire plays on the size of the passive carbon
pool. At higher fire frequencies (i.e. the number of fires over a given time period) it is
hypothesized that the passive carbon pool will increase. This is because of the addition
of black carbon. Black carbon is burnt or charred organic matter that has an exceedingly
long environmental lifetime (Masiello, 2004). For this reason black carbon is a
component of the passive carbon pool. Areas that receive more fire will have more
black carbon than those that are less affected by fire and, ultimately increase fire
frequency will increase the size of the passive carbon pool.
Fire is a disturbance that also has a high potential to influence decomposition
and nutrient cycling, which may also impact the passive carbon pool (Neary et al, 1999;
Certini, 2005). In a study conducted in the same test site as findings of this research
Reich et. al. (2001) found that rates of nitrogen mineralization and soil nitrogen
Page 6 of 38
decrease with increasing fire. Interestingly, a second hypothesis is that increase fire
frequencies will negatively affect the size of the passive carbon pool size. This is because
nitrogen has the ability to decrease breakdown of carbon stored as organic matter by
creating an environment where organic matter is not accessible to microorganisms.
To test these hypotheses different methods that are currently being used will be
analyzed in their ability to effectively quantify the passive carbon pool from the active
carbon pool. Determining the size of the passive carbon pool has been presented as a
challenge in recent years. The diverse methods that are used to separate and quantify
soil organic matter recently have been scrutinized for not yielding homogenous or
functional results (Jagadamma, 2010).This is because there are many different ways in
which carbon is stabilized in the soil. Another purpose of this study is determine if it is
appropriate to use more than one fractionating method to more accurately separate the
soil carbon pools.
Literature Review
1. Recalcitrant/ Passive Soil Carbon Pool
Nearly all carbon that enters the soil as plant residues each year either
decomposes and returns to the atmosphere or is leached from soils within a few
decades to centuries (Trumbore et al., 2008). Therefore, soil carbon is divided into
different pools based on the mean residence time. The mean residence time is defined
as the time carbon exists in the soil. Depending on the authors, pools are termed as
active, intermediate, and passive (McGill, 1996; Smith et al., 1997). However, for this
study a two pool model approach is applied. The intermediate and passive pools are
combined as one and defined as the passive carbon pool in this study. The smallest
carbon pool contains soil organic carbon with the shortest residence time (most rapid
carbon turnover rate) and is considered the active or labile carbon pool.
Page 7 of 38
The active pool exists in the soil for 1-2 years. The stable organic matter that
makes up the labile carbon pool is vulnerable to degradation because of lack of
stabilization onto mineral surfaces or lack of physical protection inside soil aggregates
(Krull et al., 2003). The other pool is characterized as the recalcitrant or passive carbon
pool and has a residence time from 10-1000s of years. The organic matter in the
recalcitrant pool is slow to decompose and therefore has a long residence time. The
passive carbon pool has a long residence time because of high molecular weight,
irregular organic matter structure, and/ or aromatic structures (Krull et al., 2003). To
better understand how the passive carbon pool behaves under different conditions a
background of key stabilizing mechanisms is essential.
Carbon stabilization is defined as the protection of organic matter from
mineralization leading to long turnover time in the soil. Processes that inhibit microbial
activity (i.e. mineralization) are mechanisms that help stabilize carbon in the soil and are
associated with the long term stabilization of soil carbon considered to be the passive
pool. The location of organic matter in the soil matrix is important decomposer
community accessibility. Soil properties such as aggregation and occlusion contribute to
the stabilization of organic matter because of the inaccessibility for microbes to attain
the soil organic carbon and convert it into atmospheric CO2 (fig. 1).
Page 8 of 38
Fig. 1. Carbon transformation pathways in soil. The scale at the bottom indicates the mean age
of organic carbon typically found in each pool. Gray arrows indicate CO2 release during
transformation from one pool to another (Trumbore and Czimczik, 2008).
2. Stabilizing Methods
2.1 Selective preservation/ Black Carbon
Selective preservation refers to the idea that some plant residues are able to
decompose more easily than others, this is because their structural composition is
considered to be less biodegradable (von Luetzow, 2007). Only a small number of
species structural formations are known, so determining the preservation from
decomposition based on plant structure is challenging. However, models have been
created to try and approximate compound classes that make up the structures.
In soils under vegetation fires recalcitrance (intrinsically resistant to
decomposition) occurs by the production of charcoal. Black carbon is another stabilizing
Page 9 of 38
factor that is considered to preserve carbon. Black carbon is burnt or charred organic
matter made from fire. Although graphite and soot particles from volatiles, and also
considered black carbon, for this study black carbon refers only to the solid residues of
char, black carbon from fire. The residence time of black carbon is estimated to be
between 500- 10000 years because of its selective preservation properties (Skjemstad et
al., 1998; Schmidt et al., 2002). Black carbon is preserved in a way in which the
compounds cannot easily be accessed by microbes it is considered carbon that is part of
the recalcitrant/ passive pool. A study conducted on a temperate mixed- grass savanna
showed that repeated fires increased the amount of black carbon in soils slightly,
contributing to the size of the passive carbon pool (Dai, 2005). Black carbon also
represented 7% of total soil organic carbon in the mixed grass savanna study, a
significant amount. In recent years, increasing attention has been given to geochemical
and biogeochemical studies of different forms of black carbon owing to their potential
importance in a wide range of processes. For example, black carbon may represent a
significant sink of the global carbon cycle (Schmidt et al., 2001), compose a useful tracer
of Earth’s fire history, and affects the Earth’s radiative heat balance (Crutzen et al.,
1990). It has even been hypothesized that black carbon may comprise a significant
fraction of the missing carbon in the global carbon budget (Kuhlbsch, 1998).
2.2 Soil Matrix
The soil matrix is the structure of the soil that includes passages for transfer of
enzymes, water, substrates, oxygen, and microorganisms. Where organic matter is
located in the soil profile, as well as the soil matrix are important because if effects the
accessibility of microorganisms to break down organic matter. Soil mineral particles
range from small particles, such as clay particles, to large soil particles. The size of the
soil particle directly relates to the size of the pore space in the soil matrix. The pore
spaces in the soil matrix serves as passageways for life to maneuver belowground. Also,
almost all organic carbon is located within the pores of the soil matrix (Krull et al., 2001).
There must be a reasonable pore space size within the soil matrix so that adequate
Page 10 of 38
quantities of water and oxygen are available for decomposition and mineralization
processes to exist (Krull et al., 2001). Pore size distribution controls occlusion of organic
matter. This is because pores are a possible habitat for microorganisms and if they are
too small microbes cannot access the carbon stored in the organic matter. Figure 2
shows how soils that have been compressed and essentially lost pore size do not
mineralize as much carbon as soils that are not compressed. Also soils that have smaller
sized particles (i.e. clay) will have a smaller area of pores space (fig. 3)
Figure 2. Changes in mineralization of C with changes in air-filled porosity and for
uncompressed and compressed soils with (a) 10% clay and (b) 28% clay (modified from
Fransleubbers, 1999 copied from Krull et al., 2001).
Figure 3. Relationship between mean residence time of 14C- labeled ryegrass incubated 6
years in soil with variable mineralogy and soil clay content (copied from Krull et al., 2001).
Page 11 of 38
Data from this experiment was collected from soil that contained very little clay.
Therefore, decomposition and mineralization was not limited because of the
architecture of the soil matrix. Because the soil in central Minnesota, Anoka County
(the site location) is derived from glacial outwash, the soil type was also constant
throughout the different burn units. The type of soil was Typic and Alfic Udpsamments.
Typic and Alfic Udpsamments is dominated by sand particles and is also known to be
infertile and well drained (Hernandez et al,, 2008). The pore size typical for sand is
between .175-.75 mm and therefore little to no aggregation (clay-like) is allowing
organic matter to be unprotected and accessible for mineralization and decomposition
of microorganisms at the study site.
2.3 Chemical Interaction with organic carbon
The soil found at Cedar Creek Ecosystem Science Reserve is well drained and
infertile. Therefore, few cations make up the minerals in the soil. However, one
chemical that is found in the soil is nitrogen. For this study looking at the effects
nitrogen has on decomposition is important. This is because repeated fire generally
reduces the soil nitrogen availability by decreasing soil pools (Reich, 2001). The effect
fire frequency has on stabilizing carbon in the soil is unknown, but the amount of
nitrogen in the soil plays a role on decomposition rates or breakdown of soil carbon.
Through an experiment conducted at the same study site of this project, Hernadez et. al.
(2008) also found that available nitrogen and phosphorus decreased with increased fire
frequency. Also it has been suggested that when nitrogen availability is high, nitrogen
reduces the amount of litter decomposition occurring (Melillo et al., 1982). Hernadez
et. al. (2001) also found that combined effects of slower rates of decomposition and
increased nitrogen immobilization that is associated with increased fire frequency, may
result in a positive feedback loop because lower amounts of nitrogen are found at
frequently burned sites (fig. 4).
Page 12 of 38
Figure 4. A positive feedback of decreased soil N availability due to fire is caused by the
immobilization of soil N into low- N litter by microbes (a), and increased N losses when fire burns
litter that has increased N content due to immobilization (b) (copied from Hernadez et al., 2008).
3. Soil Organic Matter Separation Methods
Soil organic matter is divided into different pools that are based on different
stabilization mechanisms and the residence time that they exist in the soil. For the last
two centuries soil organic matter fractionation research has undergone many different
research procedures (Olk et al., 2006). Fractionating the soil organic matter is the
separation of carbon pools. The diverse methods that are used to separate and quantify
soil organic matter have recently been scrutinized for not yielding homogenous or
functional results (Jagadamma, 2010). The various mechanisms to separate soil organic
matter can be organized into three groups: physical fractionation, chemical
fractionation, and a combination of fractionation methods.
3.1 Physical fractionation
Different physical fractionation methods all have the common goal to separate
soil organic matter into active, intermediate, and passive pools of organic carbon
matter. Aggregate fractions isolate the soil organic matter pools by means of soil
organic matter being protected and free from different organo-mineral assemblages of
different sizes and are obtained by dry and wet sieving and slaking (von Luetzow, 2007).
The idea behind separating soil aggregates by size is that soil aggregates that are small
will have longer residence times, and contribute to the passive carbon pool (Besnad et
al. 1996; Golchin et al., 1997; Puget et al., 2000).
Page 13 of 38
Particle size is based on the concept that different soil types have different
degrees of bonding affinities that relate to the sorption of soil organic matter and
therefore the type of carbon that is present (i.e. active or passive). Particle size
fractionation assumes that sorption (a physical and chemical process by which one
substance becomes attached to another) is an important stabilization mechanism for
carbon (von Luetzow, 2007). Von Luetzow found that the problem that arises when
trying to separate carbon into pools using particle size was that smaller particle sizes
was not always congruent with longer residence times and being a part of the passive
carbon pool.
Density fractionation divides soil organic matter through the use of a dense
liquid, where essentially the active pool or light fraction floats on top of the liquid and
the passive pool or heavy fraction is present in the sediment at the bottom. Density
fractionation has been used as a means to separate soil organic matter for fifty years,
however recently there has been a substantial increase in the use of the density
fractionation method (Crow et. al., 2007). Although today this method is the simplest
two pool method to separate soil organic matter, it is still only a rough differentiation
between active and passive organic matter (Crow et. al., 2007). Trumbore et al. (1989)
found that the heavy fractionation appeared to have a significant amount of fast cycling
carbon. Also, black carbon found in forests that are exposed to fire can also be present
in the the total light fraction, even though black carbon has a long residence time or
slow turnover rates and therefore belongs in the heavy fraction(von Luetzow, 2007).
Physical fractionation may be used as a useful method to differentiate soil organic
matter in the form of carbon pools initially, but results are not accurate enough for
modeling (von Luetzow, 2007; Crow et al., 2007).
3.2 Chemical Fractionation
Chemical fractionation procedures can be organized into extraction procedures,
hydrolysis of organic matter, oxidation of organic matter, and destruction of the mineral
stage. For a more detailed explanation of the different methods please refer to von
Page 14 of 38
Luetzow’s study on soil organic matter fractionation methods: Relevance to functional
pools and stabilization methods.
Oxidation of organic matter is commonly performed with hydrogen peroxide
(H2O2), NaOCl, and Na8S2O8. Oxidation is used to determine the labile carbon and stable
(non-labile) carbon. H2O2 was found to be more effective than Na8S2O8 in soils that did
not contain clay. One study conducted by Schmidt et. al. (1999) found that plant
material, lignite, charcoal and ash are all resistant to H2O2, therefore it is important to
separate the particulate organic matter before the oxidation treatment (von Luetzow,
2007). Once particulate organic matter is separated hydrogen peroxide oxidation is a
useful method to isolate the functional passive pool and make sure that no labile carbon
is present (von Luetzow, 2007).
3.3 Quantifying Black Carbon
When determining functional carbon pools a method for quantifying black
carbon has not widely been accepted. It is understood that particulate organic matter
makes up the light fraction separated by density alone; however black carbon is also
found in this fraction. Therefore, it cannot be assumed that the light fraction comprises
entirely of labile carbon, or the active carbon pool. In fact, Skjemstad et al. (1990)
exhibited that black carbon may be a major component in the light fraction. Incorrect
estimations in both the passive and active pools would be made if black carbon was not
considered in soils that have fire history.
There are numerous techniques to extract and quantify black carbon in the soil.
This study focuses on microscopic techniques to measure the number of charcoal pieces
visible under an optical microscope. Optical techniques involve the dissection of black
carbon that can detect relatively large charcoal particles (Masiello, 2004). Optical
techniques are the most appropriate to use in this study because the amount of slightly
charred biomass is predicted to change with fire frequency. The quantification of
slightly charred biomass is possible through visual/ microscopic mechanisms (area
circled in figure 5). The black carbon continuum is complex and different methods are
Page 15 of 38
associated with different regions of the continuum model (fig. 5). One method used to
quantify black carbon has not been accepted to measure all regions of the combustion
continuum, and therefore amounts of black carbon cannot be compared when
measured by different methods (Masiello, 2004). As illustrated below it is very apparent
that the black carbon that is being quantified does not represent the total continuum of
black carbon.
Fig. 5. The black carbon methods continuum (Masiello,
2004). Regions of the combustion technique are
estimated based on published results with a variety of
standards and sample types.
BPCA abbreviations
benzene polycarboxylic acids (Glaser et al., 1998)
3.4 Combination of Physical and Chemical
The challenge of finding a homogenous procedure for separating soil organic
matter stabilization lies in finding one dominant method that has the ability to
accurately separate the pools with differentiating factors of climate, soil type and
properties, mineralogy, land use, and management practices present at each site (Torn
et al., 1997: Olk and Gregorich, 2006; Sollins et al., 2006; Basile-Doelsch et al., 2009).
Also, since there are many different sources that stabilize carbon in the soil and relate to
turnover times, it is challenging to find one method that can account for diverse
stabilization factors. Although chemical extractions were more common in past years
for stable organic matter research, recently physical extractions have become more
widespread, as well as a combination of multiple methods (Olk et al., 2006).
Page 16 of 38
For this study a combination of density fractionation, hydrogen peroxide (H2O2)
oxidation chemical fractionation, and visual quantification of black carbon was used to
isolate the passive carbon pool from the total soil organic matter. Density fractionation
was chosen to separate the size of soil minerals that could contribute to the organomineral associations related to carbon stabilization. H2O2 oxidation was used to address
the degree of chemical and microbial activity that contributes to carbon stabilization. As
von Luetzow (2007) explained, plant material resists the H2O2 oxidation treatment.
Therefore, this experiment separated the particulate organic matter prior to chemically
fractionating the passive/ recalcitrant pool formed from the initial density fractionation.
Additionally the particulate organic matter or the light fraction that was separated from
the density fractionation was thoroughly examined under a microscope to remove black
carbon that may be present in the fast cycling light fraction, but is quantified with the
passive carbon pool.
The integrated approach of physical and chemical separation protocols has not
been widely studied (Jagaddamma, 2010). But, today the idea of using multiple
fractioning protocols is becoming more accepted, as more research is supporting the
idea that using one protocol alone will not accurately separate and isolate the active
and passive pools (Jagaddamma, 2010). By analyzing quantitative results, this study will
help explain the usefulness of using physical fractionation, chemical fractionation, and
visualization/ microscopic techniques to evaluate organic carbon pool sizes and
compare its effectiveness to separate active and passive carbon pools.
4. Study Site
What makes this experiment different is the known fire frequency for the past
47 years. Prior to the experiment Dai et. al. (2005) conducted, on a temperate mixedgrass savanna, no studies on recalcitrant carbon had been conducted at sites with
known recent fire histories. In 1964 Cedar Creek Ecosystem Science Reserve
implemented a prescribed burning experiment to explain ecosystem responses to fire
frequencies and to restore and maintain oak savanna vegetation (Peterson et. al., 2001).
Page 17 of 38
The 300ha area was divided into 19 management units from 2.4ha to 30ha and each
was assigned a burn frequency treatment ranging from nearly annual burns to complete
exclusion. Prior to 1964 fire history is unknown, but by studying aerial photos between
1938 and 1964 it can be hypothesized that fire occurred periodically before 1938.
Between 1938 and 1964 fire was probably suppressed because of an increasing total
canopy cover and growth of new trees. Also the area was likely periodically grazed and
experienced selective logging (Reich et al., 2001).
5. Fire Frequency
Fire has large influence on ecosystem processes, making it an important
environmental factor. The disturbance of fire has the potential to alter nutrient cycling
rates and decomposition rates (Hernadez, 2008). Also, the frequency and intensity of
fire is important because it ultimately determines the magnitude of its effect on
ecosystems (Ceterini, 2005). Still there is little understanding in the role that fire plays
on soil properties because of the uncertainty of the biogeochemical consequences
(Ansley et al., 2006). Little research (especially long term fire studies) has been
conducted on fire’s impact on ecosystems because of the lack of fire history at most
study sites (Dai et. al., 2005).
However, it is important to study the effects of fire because in recent years land
management strategies have implemented prescribed burning in some areas as well as
the suppression of fire in other areas (Neavy et. al., 1999). There is a need for more
quantitative assessments of the role fire has on grasslands and savannas (Lavorel et al.,
2001). When trying to understand the magnitude or predict the effects fire has on
ecosystems the characteristics that describe the ecosystem are important. Knowing
the frequency of the fire, season of occurrence, and the timing and duration of postfire sampling is needed to best answer uncertainties regarding the role of fire (Ansley,
2006).
Fire disturbance affects a variety of soil properties. In a study conducted by
Litton et al. (2003) soil pH increased, lower values of soil moisture were discovered, and
Page 18 of 38
organic matter content of soil was lower in plots that were burnt in a two year study. As
described previously, Hernadez et al. (2008) also found that fire influenced nitrogen
availability. With increased fire frequency nitrogen becomes volatized and promotes
nitrogen losses.
Slower rates of decomposition also occur with increase fire frequency. This is
because the immobilization of available nitrogen increases with increased fire, and
therefore nitrogen availability is not meeting the demand of the decomposer
community (Hernadez et al., 2008). Also, one study on burned and unburned tallgrass
prairies showed that immobilization of inorganic nitrogen was greater in burned site
than sites that did not receive burn treatments, hypothesizing that greater
immobilization in burned areas was due to decay of litter imputs with high C/N ratios
(Dell, 2005).
For these reasons fire may also have a significant impact on the size of the
recalcitrant/ passive carbon pool. Fire’s influence on decomposition and nutrient
cycling is a disturbance that could potentially play a large role on not only the black
carbon content, but also the global carbon cycle (Hernadez, et al., 2008). The results of
this study will provide useful information explaining fire’s affect on the global carbon
cycle.
6. Nitrogen Availability in the Soil
The role that nitrogen has on decomposition rates directly relates to nitrogen’s
effect on microbial activity in the soil. Microbes are responsible for breaking down
carbon based organic matter. The excess nitrogen found in soils that have succumbed
to fire and/ or nitrogen deposition from agriculture fields has negatively affected
microbial activity. Therefore, potentially with the inability for microorganisms to access
carbon; there will be more carbon, in the form of organic matter, in the soil when
additional nitrogen is found in the soil than is needed.
Reich et al. (2007) found that plots that had both elevated carbon dioxide and
increased nitrogen had lower photosynthetic productivity. This may suggest that areas
Page 19 of 38
where there is more carbon and nitrogen may have less biomass and ultimately a
smaller amount of total organic matter in the soil (including stable organic matter).
Methodology
1. Soil sampling
Soil samples were collected from different burn and nitrogen plots located at
Cedar Creek Ecosystem Science Reserve in Anoka County, Minnesota (45°25’N.
93°10’W) (fig. 6). Samples were extracted two months after the last burn. All the units
(with the exception of the complete exclusion units) were burnt in spring 2011. Soils at
this site are sandy, infertile, and excessively drained, Typic and Alfic Udpsamments
(Hernandez et al,, 2008). The soil of Cedar Creek is derived from glaciated outwash and
is a constant continuum among the burn gradients. Mean annual precipitation is 79 cm,
with mean daily temperatures ranging from 22°C in July to -11.5°C in January.
Prescribed burning was initiated at the site in 1964 to examine the response of
plant community to varying fire frequency and to maintain oak savanna vegetation
(Peterson and Reich, 2001). There are a total of 19 burn units at Cedar Creek. Soil was
collected from three burn units per burn frequency treatment (high, medium, low). A
total of 19 burn units ranging from 2.4 to 30 ha receive burn treatments ranging from
one per year to one per seven years to no burn control treatments. Soil was collected
from three burn units per burn frequency treatment, high, medium, low (fig. 7)
Page 20 of 38
Figure 6. Map of the location of Cedar Creek Ecosystem Science Reserve (study site), relative to
the state of Minnesota.
Page 21 of 38
Samples were also collected from a long term nitrogen deposition experiment
that was initiated in 1984 at Cedar Creek Ecosystem Science Reserve. A series of 9
different plots were placed in a 3 X 17m grid. The plots are each 1.5 X 4m and
nitrogenfertilizer (NH4NO3) is applied twice per year, once in early May and once in late
June. The different nitrogen treatments are 0, 16, and 50g/m2/yr of additive NH4NO3.
The field were this grid is located has a high burn frequency (approximately one
prescribed burn per year) that was also initiated in 1964.
Page 22 of 38
In the fire treatment and nitrogen treatment plots Quercus elliposoidalis was the
dominant tree species across all plots and therefore soil cores were extracted under the
Page 23 of 38
Burn units where soil samples were collected
Field D- Added nitrogen experiment
Figure 7. Map of Cedar Creek Ecosystem Science Reserve and the plots where soil samples were
collected. Three replicate samples were collected from each circle. Field D is the location of the
added nitrogen experiment.
canopy of large Quercus elliposoidalis individuals (diameter breast height> 25cm).
Specifically, soil samples were extracted halfway between the trunk and the drip line of
the tree. Aboveground vegetation and litter was removed from the surface before core
broke ground.
Soil cores with a 1 inch diameter were used to a depth of 15cm. Three replicate
samples were taken from each plot, and a total of nine burn plots were sampled from.
Three replicate samples were obtained from each plot.
2. Laboratory Processing and Analysis
2.1 Sieving
To remove roots and rocks samples were dried and sieved using a 2mm sieve.
Soil was then returned to the bag and homogenized thoroughly (by mixing the outside
of the bag by hand) to use for further analysis.
2.2 Gravimetric Soil Moisture
Approximately 10g of each sample was weighed and recorded and placed into a
pre-weighed aluminum tin. The tin was then placed into a 105°C oven and dried for 48
hours. The final weight was recorded and the remaining soil was air dried. Soil
moisture was then calculated.
2.3 Density Fractionation
Using a 50mL plastic centrifuge tube, 15g of air-dried, sieved soil was placed into
the centrifuge tube. Next, 30mL of sodium iodine (NaI) solution was measured in a
graduated cylinder and was also added to the centrifuge tube. This process was
repeated for each sample, a total of 18 plastic tubes. To mix the soil and NaI solution
the samples were placed on a shaker table and agitated for 16hrs. After the samples
were properly mixed the inside of the tube and cap were rinsed down with a squirt
bottle containing NaI, to ensure that all soil particles were in the NaI solution. To
Page 24 of 38
prohibit nitrogen contamination latex gloves were used at all times. The samples were
then covered with black plastic, to protect from exposure to sunlight, and settled for 48
hours.
The light fraction material, determined by what was floating ontop of the NaI,
was then removed from the mixture. As much light fraction material as possible was
first scraped out with a spatula and the rest was pipetted out and placed into another
50mL centrifuge tube, leaving only the heavy fractionation material in the original tube.
The light fraction was filtered and washed using approximately 300mL of nanopure
water with a vacuum apparatus. To avoid using carbon based equipment (i.e. filter
paper) a .45 µm nylon mesh filter paper was used. 100mL at a time was added to the
Millipore filter unit and filtered clean before another 100mL was added, and another. A
total of 300mL of nanopure was used to clean NaI from each sample. A pipette filled
with nanopure water was used to wash the edges from any light fraction that remained.
The light fraction material remaining on the filter paper was then scraped into a preweighed metal weighing dish and placed in a 65°C oven overnight and weighed the next
day. The heavy fractionation material left over in the original centrifuge tube was
filtered, washed, dried, and weighed in the same way as the light fraction material.
2.4 H2O2 Oxidation
To further extract active cycling carbon from the heavy fractionation material a
chemical method was applied to the heavy fraction. Using H2O2 as the oxidizing agent,
one gram of the heavy fractionation was wetted with 10mL of distilled water for 10
minutes. 30mL of 10% H2O2 was added to the material and once the intense initial
reaction ceased the oxidation continued in 50°C water bath (Jagadamma, 2010). The
frothing eventually subsided completely (approximately 2-3 days) and the suspension
was centrifuged at 2500g × g for 15 minutes and the supernatant was poured.
Oxidation was repeated twice for each heavy fractionation sample.
Page 25 of 38
2.5 Quantification of black carbon
Light fractionation material was placed under a light microscope, high power
(400X) and burnt or charred material was removed with tweezers. This material is
considered black carbon and was quantified with the heavy fractionation, since it is
considered part of the stable carbon pool. The rest of the light fractionation was
weighed as the labile carbon pool (Skjemstad, 2002).
2.6 Statistical analysis
The analysis of variance (ANOVA) was used to test the effectiveness of the
different methods in extracting the carbon from the passive pool. A linear regression
model was used to show the relationship between nitrogen, fire, and the quantity of the
passive carbon pool in the soil. A P-value was obtained to show the statistical
significance at a 95% confidence level of the linear regressions.
Results
The integration of different methods was important in quantifying the amount of
stable carbon in the soil. Figure 8 shows the weight of carbon in the heavy fraction
when the only method that was applied was the density fractionation with sodium
iodine. The effect fire frequency had on the heavy fraction was not statistically
significant (p- value= 0.568). Also a large portion of active cycling carbon was removed
from the initial density fractionation samples. The soil samples that were collected from
the nitrogen gradient plots and were separated with NaI, through the density
fractionation method, was statistically significant (fig 8), with a p- value of 0.067.
However, a large amount was removed from that initial heavy fraction weight.
Page 26 of 38
Figure 8. The linear regressions depict the relationship between the amount of carbon in the
stable pool (described as HF: heavy fraction, before chemical fractionation) between fire
frequency and nitrogen content. R2 value of nitrogen content shows that the relationship is
statistically significant, p value= 0.067. The relationship between burn frequency and the
passive pool (r2 value= 0.029) was not significant at a 95% confidence level (p- value= 0.568).
Page 27 of 38
As fire frequency increased, the size of the passive carbon pool also increased
(fig. 9). A linear regression model was used to find the relationship between fire
frequency and the passive carbon pool and an r2 value of 0.0396 was calculated. A
statistical analysis was applied and a p- value of 0.319 was obtained. Although these
findings are not statistically significant (confidence level of 95%), there is a visible trend
that the passive carbon pool increases with increased frequency of fire.
Figure 9. The linear regression explains the relationship between the fire frequency (burn range
from 0.33-0.88 occurences/ year) passive carbon pool (g of carbon/ total soil organic matter kg).
The p-value shows that the relationship is not statistically significant at the 95% confidence level
(p- value= 0.319)
The same approach to compare fire frequency was also used to show the
relationship between amounts of nitrogen in the soil and the passive carbon pool. The
linear regression model clearly indicates that the amount of nitrogen in the soil
contributes to decreasing the size of the passive carbon pool (r2 value= 0.06659).
Nitrogen in the soil also had a significant impact on the amount of stable carbon found
in the passive carbon pool. Fig. 10 shows as more nitrogen is added to the soil, the
Page 28 of 38
amount of carbon in the soil decreases. The results of a statistical analysis shows that
these findings are also very significant at a 95% confidence level (p- value= 6.77E-20).
Figure 10. A linear regression analyis was applied to determine signifcance of the relationship
between nitrogen, quantified in g/m2/ year and the quantification of the passive carbon pool.
The regression was significant (p- value= 6.77E-20).
One goal of this project was to assess the realability and effectiveness of a
combination of methods used to isolate and quantifythe passive carbon pool. The mean
and standard deviation of the amount of stable carbon in each pool was quantified and
graphed (fig. 11). After the initial physical fractionation of light and heavy fractions the
light fraction underwent a chemical oxidation using H2O2 and a significant amount of
active oxidized carbon was removed from the initial physical density fractionation. The
pool size of chemically stabilized soil organic carbon was substaintly lower than that of
phsically stabilized soil organic carbon (37.1% of the physical density fractionation). On
avergae the heavy fractionation had 9.37 g C kg-1soil more than the light fraction after
Page 29 of 38
initial density fractionation. When analyzing the standard deviation the amount of black
carbon quantified was not significat when removed from the light fractionation
(standard deviation (SD= +- 0.10).
Figure 11. Histogram of the mean amount of carbon removed when applied to each methods. The carbon
retrieved for the chemical H 2O2 oxidation (SD= +- 1.7) method was extracted from the physical density
fractionation HF (heavy fraction), SD = +- 2.5. The black carbon (SD= +- .08) was removed from the
physical seperation LF (light fraction), SD= +-.08). Statistically different methods (at P<0.05) were physical
density fractionation HF and chemical H2O2 oxidation. The physical seperation LF and black carbon
removal was not significant.
Discussion
1. Fire Frequency Effects on Recalcitrant/ Passive Carbon Pool
Recalcitrant carbon increased subtly with increasing fire frequency. As predicted
the amount of carbon in the passive pool increased with fire frequency. When the heavy
Page 30 of 38
fraction of the soil sample was only quantified (fig. 8) there was no relationship between
burn frequency and the passive carbon pool, however with the inclusion of black carbon
in the heavy fraction (fig. 9) there was a slight increase of the passive carbon pool with
increase burn frequency. The data collected supports the prediction that the passive
carbon increases with the addition of black carbon. Dai et al. (2005) also found that
repeated fires increased the amount of black carbon slightly in the soil at a soil depth of
10- 20cm. However, it is difficult to compare results when different methods were used
to measure the fractions of the BC continuum (Schmidt et al., 2001). Dai et al. (2005)
used benzenepolycarboxylic acids (BCPA) as molecular markers to analyze black carbon.
Today,continued research on a universial and accurate method to quantify blackc arbon
is still being researched. Black carbon represented a significant amount of the
recalcitrant SOC pool and the findings of this study suggest that when fire is prevelant in
an ecosystem modeling the recalcitrant SOC pool is strongly dependent on analyzing
black carbon.
Another study that looked at fire frequency and the black carbon also found
similar results (Eckmeier et al., 2007). Eckmeier et al. (2007) explained that only small
concentrations of charcoal were detectable after one year of a fire occurrence.
2. Nitrogen Effects on Recalcitrant/ Passive Carbon Pool
The recalicitrant pool showed a decrease in size at higher nitrogen
concentrations. It was hypothesized that there would be more carbon in the passive/
recalcitrant pool at higher nitrogen concentrations. However, these findings support
the idea that the passive carbon pool increases with fire frequency. At higher burn
frequenies there is less available nitrogen for the microbial community (Hernandez,
2008) and according to the findings from this study the passive carbon pool is larger at
lower nitrogen concentrations. Increased amounts of nitrogen may negatively effect the
decomposition rate (Reich, 2001) for organic matter, but microbes may begin to access
the passive carbon pool when there is more nitrogen instead, leading to a smaller
passive carbon pool.
Page 31 of 38
3. Methodology to Isolate the Recalcitrant/ Passive Carbon Pool
An integrated method approach was used to separate the recalcitrant carbon
from all other carbon. There was a substantial amount of active cycling carbon that was
removed from the initial heavy fraction when the oxidation method was applied.
Jagadamma (2010) also found the stable organic matter isolated by phyiscal methods
was substanially more than when the pool was isoloated by chemical oxidation using
H2O2.
Due to lack of funds and accesibility, the method used for quanitifying black
carbon was not as accurate as it could have been. The amount of black carbon that was
recovered from the light fraction was not statistically significant. Jagadamma (2011)
also found the removal of black carbon through chemical means to not be significant in
total stable soil organic quantification.
Conclusion
The analysis of the recalcitrant/ passive carbon pool clearly gave useful insight
on the effects certain environmental factors have on the carbon in the soil. In this
study, both increased nitrogen and fire frequency affected the size of the passive carbon
pool. Increased burn occurrences across an oak savanna increased the size of stable
carbon held underground, while soils that had a greater application of nitrogen had a
smaller amount of stable carbon than soils that had less nitrogen.
This analysis also showed that combining physical and chemical methods is
important to accurately quantify the recalcitrant carbon in the soil. Accurately
quantifying stable soil carbon is difficult because many factors contribute to carbon
stabilization. Therefore, more research should be conducted on the factors that create
some carbon to remain in the soil for a long period of time, and some carbon to cycle
quickly out of the soil and into the atmosphere. Methods to quantify carbon in the soil
need to be addressed, so that scientist can compare results and accurate results are
being obtained. Ansley et al., (2006) found that seasonal variance of when fires
occurred had an effect on the stable organic matter in the soil. Also the depth of the
Page 32 of 38
soil profile influenced the amount of stable organic matter. Further research on the
timing of the fire during the year and soil samples collected at deeper soil depths may
alter the results of this study.
Recently, land management programs have been organizing prescribed burns to
help restore, suppress the spread of certain plant species, and conserve prairie areas
around neighborhoods and parks. Because there is an increase of control burns to
manage prairies, the methods used from this study would also be sufficient on prairie
ecosystems. Further research could include the retention of stable organic matter in
tall and short prairies with change of fire frequency.
Nonetheless, the results of this study will provide useful information to land
managers, policy makers, and scientists who are now evaluating the potential for land
management practices to alter ecosystem carbon storage and influence atmospheric
CO2 concentrations and global climate. Specifically, this study provides implications on
belowground mechanisms of the global carbon cycle with respect to fire frequency. The
results may help fill in uncertainties in the carbon cycle with respect to belowground
carbon storage.
Page 33 of 38
Acknowledgements
Thank you Charlotte Riggs (University of Minnesota) and Dr. Rubinfeld (Carthage
College) for help with method development and advice. Dr. Sarah Hobbie (University of
Minnesota) for allowing me to use her laboratory and equipment. And Cedar Creek
Ecosystem Science Reserve for permitting me to take soil samples.
Page 34 of 38
References
Ansley, R, Boutton, T, Skjemstad, J. (2006) Soil organic carbon and black carbon storage
and dynamics under different fire regimes in temperate mixed-grass
savanna.Global Biogeochemical Cycles 20, B3006.
Basile- Doelsch I, Brun T, Borschnech D, Massion A, Marol C, Baldesdent J. (2009)
Effects landuse on organic matter stabilized in organomineral complexes: A
study combining density fractionation, mineralogy and δ13C. Geoderma 151, 7786
Brown T, Hall B, Westerling A. (2004) The impact of twenty-first
century climate change on wildland fire danger in the western United
States: An applications perspective. Climatic Change 62:365-388.
Crow S, Swanston C, Lajtha K, Brooks J, Keirstead H. (2007) Density fractionation of
forest soils: methodological questions and interpretation of incubation results
and turnover time in an ecosystem context. Biogeochemistry 85(1): 69-90
Crutzen P, Andreae M. (1990) Biomass burning in the tropics: impact on atmospheric
chemistry and biogeochemical cycles. Science (New York, N.Y.) 250(4988): 16691678
Dell C and Rice C. (2005), Short-term competition for ammonium and nitrate in tallgrass
prairie, Soil Sci. Soc. Am. J., 69, 371 – 377.
Eckmeie E, Gerlach R, Skjemstad J, Ehrmann O, Schmidt M. (2007) Only
small changes in soil organic carbon and charcoal found one year after
experimental slash-and-burn in a temperate deciduous forest. Biogeosci.
Discuss 4, 595–614.
Page 35 of 38
Hernandez D, Hobbie S. (2008) Effects of fire frequency on oak litter decomposition and
nitrogen dynamics. Oecologia
158:535–43.
Jagadamma S, Lal R. (2010) Integrating physical and chemical methods for isolating
stable soil organic carbon. Geoderma 158(3-4): 322-330
Krull S, Baldock J, Skjemstad J. ( 2001) Soil texture effects on decomposition and soil
carbon storage. Kirschbaum, M.U.F., Mueller, R. (Eds.), Net Ecosystem Exchange
CRC Workshop proceedings. CRC forGreenhouse Accounting, Canberra, pp. 103–
110.
Krull E, Swanston C, Skjemstad J, McGowan J. (2006) Importance of charcoal in
determining the age andchemistry of organic carbon in surface soils. J. Geophys.
Res.111, G04001.
Kuhlbusch T. (2007) Black carbon and the carbon cycle. Science 1998a; 280:1903 – 4.
Litton C, Santelices R. (2002) Early post- fire succession in a Nothofagus glauca forest in
the Coastal Cordillera of south- central Chile. International Journal of Wildland
Fire 11, 115- 125
Lützow, M, Kögel-Knabner I, Ekschmitt K, Matzner E, Guggenberger G, Marschner B.
Flessa H. (2006) Stabilization of organic matter in temperate soils: mechanisms
and their relevance under different soil conditions – a review. European Journal
of Soil Science, 57: 426–445. doi: 10.1111/j.1365-2389.2006.00809.x
Marschner B, Brodowski S, Dreves A, Gleixner G, Gude A, Grootes PM, Hamer U, Heim A,
Jandl G, Ji R, Kaiser K, Kalbitz K, Kramer C, Leinweber P, Rethemeyer J, Schaeffer
A, Schmidt M, Schwark L, Wiesenberg G. (2008) How relevant is recalcitrance for
Page 36 of 38
the stabilization of organic matter in soils? Journal of Plant Nutrition and Soil
Science-Zeitschrift Fur Pflanzenernahrung Und Bodenkunde 171(1): 91-110
Masiello C. (2004) ‘New directions in black carbon organic geochemistry’, Marine
Chemistry 92, 201–213.
Melillo J, Aber J, Linkins A, Ricca A, Fry B, Nadelhoffer K. (1989) Carbon and nitrogen
dynamics along the decay continuum: plant litter to soil organic matter. Plant
and Soil, 115, 189–198.
Neary D, Klopatek C, Debano L, Folliott P. (1999) Fire effects on belowground
sustainability: a review and synthesis. For Ecological Management 122:51–71.
Olk D, Gregorich E. (2006) Meaningful pools in determining soil carbon and nitrogen
dynamics". Soil Sci. Soc. Am. J 70: 967-974.
Reich P, Hungate B, Luo Y. (2007) Carbon- nitrogen interactions in terrestrial
ecosystems in response to rising atmospheric carbon dioxide. Ecology 27: 61136.
Reich P, Peterson D, Wedin D, Wrage K. (2001) Fire and vegetation effects on
productivity and nitrogen cycling across a forest grassland continuum. Ecology
82:1703–1719
Schmidt M, Skjemstad J, Czimczik C, Glaser B, Prentice K, Gelinas Y, Kuhlbusch, T. (2001)
Comparative analysis of black carbon in soils. Global Biogeochemical Cycles, 15,
163–167.
Page 37 of 38
Skjemstad J, Reicosky D, Wilts A, McGowan A. (2002) ‘Charcoal carbon in U.S.
agricultural soils’, Soil Science Society of America Journal 66, 1249–1255.
Sollins P, Swanston C, Kramer M. (2007) Stabilization and destabilization of soil organic
matter - a new focus. Biogeochemistry 85(1): 1-7
Torn M, Trumbore S, Chadwick O, Vitousek P, Hendricks D. (1997) Mineral control of
soil organic carbon storage and turnover. Nature 389:170–173.
Trumbore S, Czimczik C. (2008) Geology - An uncertain future for soil carbon. Science
321(5895): 1455-1456
Trumbore S, Vogel J, Southon J. (1989) AMS 14C measurements of fractionated soil
organic matter: an approach to deciphering the soil carbon cycle, Radiocarbon
31: 644-654.
von Lutzow M, Koegel-Knabner I, Ekschmitt K, Flessa H, Guggenberger G, Matzner E,
Marschner B. (2007) SOM fractionation methods: Relevance to functional pools
and to stabilization mechanisms. Soil Biology & Biochemistry 39(9): 2183-2207
von Lutzow M, Kogel-Knabner I, Ludwig B, Matzner E, Flessa H, Ekschmitt K,
Guggenberger G, Marschner B, Kalbitz K. (2008) Stabilization mechanisms of
organic matter in four temperate soils: Development and application of a
conceptual model. Journal of Plant Nutrition and Soil Science-Zeitschrift Fur
Pflanzenernahrung Und Bodenkunde 171(1): 111-124
Peterson D, Reich P. (2001) Prescribed Fire in oak savanna: Fire frequency
effects on stand structure and dynamics. Ecol. Appl., 11:914–927
Page 38 of 38