SOIL ORGANIC CARBON FRACTIONS AND CARBOHYDRATE
HYDROLASE ACTIVITY IN A FOREST ECOSYSTEM
FOLLOWING PRESCRIBED BURNING AND THINNING
by
DESSY ACHIENG OWITI
A THESIS
Submitted in partial fulfillment of the requirements for
the degree of Master of Science
in the Department of Biological and Environmental Sciences
in the School of Graduate Studies
Alabama Agricultural and Mechanical University
Normal, Alabama 35762
December 2014
Submitted by DESSY ACHIENG OWITI in partial fulfillment of the
requirements for the degree of MASTER OF SCIENCE specializing in PLANT AND
SOIL SCIENCE.
Accepted on behalf of the faculty of the Graduate School by the Thesis
Committee:
Dr. Elica M. Moss
Dr. Zachary Senwo
Dr. Irenus Tazisong
Major Advisor
Dr. Regine Mankolo
Dean of the Graduate School
Date
ii
Copyright by
DESSY ACHIENG OWITI
2014
iii
I dedicate this thesis to my family and everyone who contributed in making it a success.
iv
SOIL ORGANIC CARBON FRACTIONS AND CARBOHYDRATE
HYDROLASE ACTIVITY IN A FOREST ECOSYSTEM
FOLLOWING PRESCRIBED BURNING AND THINNING
Owiti, Dessy, M.S., Alabama A&M University, 2014. 81 pp.
Thesis Advisor: Dr. Irenus Tazisong
United States Department of Agriculture Forest Service applied prescribed
thinning and burning for forest restoration and regeneration following the detrimental
southern pine beetle (Dendroctonus frontalis Z) epidemic at Bankhead National Forest.
Fire regimes were imposed as: frequent fire (every 3 years), infrequent fire (every 9
years), and unburned control. This study evaluated the impact of prescribed burning and
thinning on: (I) labile organic carbon fractions, (II) carbohydrate hydrolases activities,
and (III) potential carbon mineralization and components of dissolved organic matter.
Soils were collected from 0 to 10 cm depth in three replicates. Labile organic
carbon was isolated using the density method whereas carbohydrate hydrolases activities
were determined as described in Methods in Soil Enzymology, and Methods of Soil
analysis, Part 2: Microbiological and biochemical properties.
Microbial biomass carbon ranged from 618 ± 318 (light thin + burn) to 1335 ± 91
g kg-1(reference plot). Heavy thin + burn treatment (1334 ± 650 g kg-1) insignificantly
increased particulate organic carbon content compared to the reference plot (667 ± 160 g
kg-1). Light fraction carbon was 63.26% more in light thin treated plot than in the
reference plot. Correlation analysis revealed a significant negative relationship between
amino acid with xylanase and invertase. Particulate organic carbon and light fraction
carbon were significantly correlated with amylase, β-glucosidase and NAGase.
v
Irrespective of treatment, enzyme activity was in the order, xylanase > invertase >
cellulase > NAGase > β-glucosidase > amylase. Protein content was not detected despite
an appreciable amount of amino acid content in soil.
KEY WORDS: carbon enzymes, microbial biomass, light fraction, potential carbon
mineralized, dissolved organic matter.
vi
TABLE OF CONTENT
CERTIFICATE OF APPROVAL.......................................................................................ii
ABSTRACT AND KEY WORDS......................................................................................v
LIST OF TABLES..............................................................................................................ix
LIST OF FIGURES.............................................................................................................x
ACKNOWLEDGEMENTS...............................................................................................xii
CHAPTER 1 - INTRODUCTION.......................................................................................1
Rationale..................................................................................................................4
Research Objectives.................................................................................................5
CHAPTER 2 - LITERATURE REVIEW............................................................................6
Microbial Biomass Carbon......................................................................................8
Particulate Organic Matter.......................................................................................9
Light Fraction.........................................................................................................10
Cellulase and Beta- D- glucosidase.......................................................................13
Invertase.................................................................................................................14
N-acetyl-β-D- glucosidase.....................................................................................14
Xylanase.................................................................................................................15
Amylase.................................................................................................................16
vii
Potential Carbon Mineralized................................................................................17
Dissolved Organic Matter......................................................................................19
CHAPTER 3 - MATERIALS AND METHODS..............................................................21
Study Site...............................................................................................................21
Experiment Design.................................................................................................23
Soil Sampling and Analysis...................................................................................24
Objective 1: Determine the Effect of Prescribed Burning and Thinning on Labile
Organic Carbon Fractions......................................................................................25
Objective 2: Study the Impact of Prescribed Burning and Thinning on
Carbohydrate Hydrolases Activities......................................................................27
Objective 3: Evaluate the Effect of Prescribed Burning and Thinning on
Potential Carbon Mineralization and Components of Dissolved Organic
Matter.....................................................................................................................32
Statistical Analysis.................................................................................................37
CHAPTER 4 - RESULTS AND DISCUSSIONS.............................................................38
The Effect of Prescribed Burning and Thinning on Labile Organic Carbon
Fractions in a Forest Ecosystem............................................................................40
The Impact of Prescribed Burning and Thinning on Carbohydrate Hydrolases
Activities in a Forest Ecosystem............................................................................48
The Effect of Prescribed Burning and Thinning on Potential Carbon
Mineralization and Components of Dissolved Organic Matter ............................62
CHAPTER 5 - CONCLUSION.........................................................................................69
REFERENCES..................................................................................................................72
VITA......................................................................................................................................
viii
LIST OF TABLES
Tables
Page
1.
Treatment applications at Bankhead National Forest............................................23
2a.
Soil properties used................................................................................................39
2b.
Soil properties used................................................................................................41
3.
Correlation analysis between enzyme activities and labile carbon fractions.........61
4.
Correlation analysis between enzyme activities and soil properties......................62
ix
LIST OF FIGURES
Figures
Page
1.
Map of the Bankhead National Forest showing treatment stands..........................22
2.
Microbial biomass carbon content at 0-10 cm soil depth following various
treatment applications at Bankhead National Forest.............................................42
3.
Particulate organic carbon content at 0-10 cm soil depth following various
treatment applications at Bankhead National Forest.............................................44
4.
Picture of extracted light fraction carbon from soil...............................................46
5.
Light fraction carbon content at 0-10 cm soil depth following various treatment
applications at Bankhead National Forest..............................................................47
6.
Cellulase activity in soil at 0-10 cm soil depth following various treatment
applications at Bankhead National Forest..............................................................49
7.
Beta-Glucosidase activity in soil at 0-10 cm soil depth following various
treatment applications at Bankhead National Forest.............................................51
8.
Invertase activity in soil at 0-10 cm soil depth following various treatment
applications at Bankhead National Forest..............................................................52
9.
NAGase activity in soil at 0-10 cm soil depth following various treatment
applications at Bankhead National Forest..............................................................54
10.
Xylanase activity in soil at 0-10 cm soil depth following various treatment
applications at Bankhead National Forest..............................................................55
11.
Amylase activity in soil at 0-10 cm soil depth following various treatment
applications at Bankhead National Forest..............................................................57
12.
A comparison between enzyme activities subjected to various treatments at
Bankhead National Forest......................................................................................58
x
13.
A comparison between enzyme activities subjected to various treatments at
Bankhead National Forest......................................................................................60
14.
Potential carbon mineralized at 0-10 cm soil depth following various treatment
applications at Bankhead National Forest..............................................................64
15.
Phenol content at 0-10 cm soil depth as impacted by various treatment
applications at Bankhead National Forest..............................................................65
16.
Hexose content at 0-10 cm soil depth as impacted by various treatment
applications at Bankhead National Forest..............................................................66
17.
Amino acid content at 0-10 cm soil depth as impacted by various treatment
applications at Bankhead National Forest..............................................................68
xi
ACKNOWLEDGEMENTS
I would like to express my sincere appreciation to my advisory committee
members Dr. Zachary Senwo, Dr. Regine Mankolo, Dr. Elica Moss and especially Dr.
Irenus Tazisong for serving as the chairperson for the committee, and whose dedication
led to the accomplishment of this work.
I also wish to extend my sincere gratitude to Dr. Fritz Ntoko and Garret Hayzer
who assisted me in interpreting data using software and assisted with partial editing of
this work. I would also like to thank my professors, staff, graduate students, and my
laboratory colleagues in the department of Soil and plant science for their contributions in
making this work a success. Funds for this project came from the department of
Biological and Environmental Sciences through NSF CREST- CFEA award# 1036600
xii
CHAPTER 1
INTRODUCTION
Reforestation was employed at Bankhead National Forest (BNF) in the 1930s and
1960s, whereby hardwood stands were replaced with fast growing loblolly pine stands
(Pinus taeda L.) to improve the forest economic yields (Gaines and Creed, 2003). The
subsequent density increase of loblolly pine stands (Pinus taeda L.) contributed
substantially to the infestation of southern pine beetle (Dendroctonus frontalis Z) at
epidemic levels (Gaines and Creed, 2003). The epidemic peaked in 2000 and continued
at very high levels through 2001, causing mortality of loblolly pine (Pinus taeda L.) and
consequently, large areas of standing dead trees, that were a public safety hazard and a
fire hazards (Gaines and Creed, 2003).
The United States Department of Agriculture (USDA) Forest Service began
silvicultural treatments (prescribed thin and prescribed low intensity, low frequency
understory burn) in the forest. The aim was to reduce the beetle infestation, reduce fuel
loads, increase general forest productivity to enhance plant and animal diversity, and to
gradually replace existing pine stands with native hardwood plants such as dry and xeric
oak forest, dry mesic oak and oak pine forest (Gaines and Creed, 2003).
1
In the extensively managed pine plantations in southern USA, the effect of using
prescribed fire as a management technique can be assessed directly through tree
mortality, growth, radial increment yield and rotation time (Boerner et al., 2000). In
contrast, in less intensively managed forest, determining the degree to which the less
clear-cut goals of longer-term conservation projects have been achieved is difficult
(Boerner et al., 2000).
Successful restoration and regeneration of a terrestrial ecosystem’s structure and
function highly depends on the efficacy of nutrient cycling, and carbon is one of the
elements involved in that cycle. Maintaining its stock is vital for forest productivity for
two main reasons. (i) it is a major element of dry mass biomass of most soil organisms
and a principal component of soil organic matter (Wagner and Wolf, 1998; Nave et al.,
2010). (ii) It is assimilated by soil organisms that mediate degradation processes and
facilitate nutrient distribution (Wagner and Wolf, 1998; Wander, 2004). The microbes
use it for energy production and for the synthesis of cellular constituents necessary for
growth, survival and reproduction (Wagner and Wolf, 1998).
Assessing soil organic carbon (SOC) dynamics and the activities of enzymes that
catalyze their degradation may provide insight into how silvicultural treatments influence
nutrient cycling and subsequently, terrestrial ecosystem's productivity. Soil organic
carbon is a heterogeneous mixture of organic carbon substances that can be partitioned
into fractions such as: labile, intermediate and recalcitrant pools (González-Pérez et al.,
2004; Wander, 2004). The labile carbon fractions are characterized by rapid
mineralization and lack of protection by soil colloids (Wander, 2004). These
characteristics render them highly sensitivity to soil changes (Wander, 2004).
2
As a result, they often hold as a potential index for assessing the impact of
manipulative treatments on soil organic matter quality, quantity, and subsequently
nutrient cycling (Wan et al., 2001; Fynn et al., 2003; Andersson et al., 2004; AcostaMartinez and Harmel, 2006). Although most studies unanimously report a decrease in
SOC immediately post prescribed burning and/or thinning, reports on the long-term
effects vary tremendously.
Some investigators have reported a decrease in SOC after burning and/or thinning
treatment application (Pietikainen, 1995; Bird et al., 2000; Johnson and Curtis, 2001;
Fynn et al., 2003; Yang et al., 2009;). Reduction in carbon inputs results from the
volatilization or vegetation removal after burning and/or thinning may cause SOC
depletion (Pietikainen, 1995; Bird et al., 2000).
Increased SOC has been attributed to the incorporation of burned plant biomass in
soil (Nobles et al., 2009). In other cases, the increase has been because of rapid
decomposition of organic matter due to ameliorated soil properties such as increased pH,
readily available substrate, and nutrient released from organic matter decomposition
(Pietikainen, 1995; Andersson, 2004; Saarsalmi et al., 2004). Other investigators
observed no statistically significant effect of thinning/harvesting treatments on SOC, a
possible indication that treatments had a neutral effect (Johnson and Curtis, 2001).
Differences in vegetation, topography, and timing or depth of soil sampling may
explain variations in reports (Wan et al., 2000; Johnson and Curtis, 2001; Fynn et al.,
2003). Different thinning intensity, time since harvest and fire regimes (e.g. frequency,
intensity, season of fire and time since fire) could explain variations in reports (Johnson
and Curtis, 2001).
3
Enzymes, primarily of microbial origin, are important indices for assessing the
impact of perturbations such as prescribed burn and/or thin (Bandick and Dick, 1999).
They are important because they account for carbon cycling by catalyzing the
degradation process (Bandick and Dick, 1999; Rietl and Jackson, 2012). They reflect the
impact of management practices on the activity of diverse microbial assemblages (Rietl
and Jackson, 2012). Due to their sensitivity, they respond rapidly to environmental
changes attributed to management practices (Eivazi and Bayan, 1996; Chanders et al.,
1997; Bandick and Dick, 1999; Acosta-Martinez et al., 2007; Hamman et al., 2008).
The initial negative response of enzyme activities immediately post burn and/or
thin treatments have been associated with decreased microbial biomass (Pietikäinen and
Fritze, 1995; Andersson et al., 2004). The depletion may also be because of changes in
substrate availability due to altered soil organic matter quantity and quality (Bandick and
Dick, 1999). On the contrary, the long-term effects of burning and thinning treatment
vary.
Rationale
The widespread adoption of slash and burn clearing practices alter not only the
highly efficient nutrient-conserving mechanisms that characterize a forest, but also the
patterns of SOM cycling and enzymatic activities within the ecosystem (Garcia-Montiel
et al., 2000). Considering the role of forest ecosystems on global biogeochemical cycles,
elemental transformation and enzyme activity are primary in predicting nutrient
availability, as well as air, soil and ground water quality.
4
Shortly after burn clearing in a forest, significant depletion of SOM occurs, and
thus may affect the enzyme activities that are primarily responsible in nutrient cycling.
The long-term effects of repeated burn and clearing in forest ecosystems are scanty. This
study will bridge this knowledge gap by providing an understanding of SOM
transformations and microbial processes in a repeatedly burned and thinned forest
ecosystem.
Research Objectives
Prescribed fire and logging treatments applied to forest ecosystem are considered
to have short and long-term effects on biological, chemical and physical properties that
influence the soil nutrient cycles essential to long-term sustainability of forest
ecosystems. While our understanding of carbon forms and the microbial ecology
responsible for carbon cycling in agro-ecosystems have improved, more research needs to
be done on forest ecosystems. Therefore, the objectives of this study were to:
1. Determine the effect of prescribed burning and thinning on labile organic carbon
fractions in a forest ecosystem.
2. Study the impact of prescribed burning and thinning on carbohydrate hydrolases
activities in a forest ecosystem.
3. Evaluate the effect of prescribed burning and thinning on potential carbon
mineralization and components of dissolved organic matter.
5
CHAPTER 2
LITERATURE REVIEW
Fire is a powerful and instantaneous modifier of the environment with potential to
influence nutrient cycles in ecosystems (Wan et al., 2001). In addition, fire can influence
plant growth as well as species composition and activity (Wan et al., 2001; Nobles et al.,
2009). Under intense fire, nutrient cycling can be diminished due to microorganism
mortality; reduced enzyme activity; and nutrient loss through volatilization, oxidation,
leaching and soil erosion (Poff, 1996; Gutknecht et al., 2010). Prescribed fires are often
less intense and severe because they are carried out under high humidity, low temperature
and low wind speeds (Poff, 1996).
Depending on the intensity, prescribed thinning applications can cause beneficial
or detrimental effects on nutrient cycling and, consequently, nutrient productivity. The
treatment may alter substrate inputs, organic matter turnover, soil microbial communities
and the microclimate conditions that drive plant and microbial processes (Poff, 1996;
Nave et al., 2010; Geng et al., 2012). Detrimental effects from thinning can result from
erosion, displacement, compaction, biomass export and leaching (Poff, 1996). The
treatment may induce beneficial results by enhancing microclimate conditions such as
increased soil temperature and moisture (Poff, 1996; Maassen et al., 2006).
6
Increased temperature and moisture are often as a result of increased direct sunlight and
higher throughfall (Poff, 1996; Maassen et al., 2006). In addition to intensity and
severity, the frequency of burning and thinning treatments greatly influences the efficacy
of management techniques in restoring and regenerating forest ecosystems (Wang et al.,
2012).
Prescribed thinning and a low intensity, understory prescribed burn are often
applied by forest management personnel to improve terrestrial ecosystems (Hubbard et
al., 2004). Application of these techniques are postulated to mitigate wild fires by fuel
reduction and also to restore degraded forest by improving productivity, wildlife habitat
and maintaining species composition (Wade and Lunsford, 1989; Pietikainen et al., 1995;
Hubbard et al., 2004). Burning has also been used in forest to raise soil pH, cation
concentrations, and to prevent soil acidity (Viro, 1974; Macadam, 1987; Pietikaine and
Fritze, 1994). At the Bankhead National Forest, management techniques were adopted to
counteract the negative impact induced by the pest invasion.
In this study we assessed the impact of those management techniques, repeated
burning and thinning, on the transformation of various soil organic matter fractions. We
evaluated potential carbon mineralized (PCM), quantified the availability of dissolved
organic matter components (DOM) and assessed the quantity of labile carbon fractions.
The labile carbon fractions assessed were light fraction carbon (LFC), microbial biomass
carbon (MBC) and particulate organic carbon (POC). The dissolved organic matter
components evaluated in this study were phenol, hexose, amino acids and proteins.
7
Microbial Biomass Carbon
Soil microbial processes facilitate nutrient cycling and productivity through
processes such as degradation of organic residue, transformation of soil organic matter,
mineralization and immobilization of nutrients, and formation and stabilization of soil
aggregates (Nsabimana et al., 2004; Bonglovanni and Lobartini, 2006; Yang et al., 2010).
Microbial biomass is the living component of soil organic matter and it typically
comprises of 1-5% of total organic matter content, 2-3% of soil carbon and 3-5 % of soil
nitrogen (McGill et al., 1986; Nsabimana et al., 2004). Quantification of microbial
biomass following perturbations is essential for three main reasons. (i) Microorganisms
mediate the conversion of plant nutrients from stable organic forms to available mineral
forms over long periods (McGill et al., 1986). (ii) In the short term, microbial biomass
carbon serves as a source and sink of mineral nutrients and organic substrates (McGill et
al., 1986). (iii) Microbial biomass carbon has a fast turnover rate and therefore responds
rapidly to changes in soil management practices (Nsabimana et al., 2004).
Changes resulting from disturbances such as thin and burn treatments are often
the consequences of direct or indirect effects (Pietikainen and Fritze, 1995; Williams et
al., 2012). Direct effects of treatments include (i) heat induced death, (ii) mortality due to
toxic compounds produced during combustion, and (iii) radiation from the sun following
plant cover removal (Andersson et al., 2004; González-Pérez et al., 2004; Williams et al.,
2012; ). Indirect effects following treatment applications are often because of changes in
environmental and edaphic factors (Andersson et al., 2004; Mahía et al., 2006).
8
Examples of such changes include modifications of moisture, temperature, pH, and
substrate quality and quantity (Pietikainen and Fritze, 1995; Thibodeau et al., 2000;
Andersson et al., 2004; Mahía et al., 2006; Wang et al., 2012).
The responses of MBC to prescribed treatments are inconsistent. Some studies
have reported an increase, a decrease and others no change in MBC (Pietikainen and
Fritze, 1995; Eivazi and Bayan, 1996; Maassen et al., 2006; Chatterjee et al., 2008; Wang
et al., 2012; Geng et al., 2012). The inconsistency has been attributed to frequency,
severity and intensity of treatments, time since treatments applications, and reduced or
increased organic biomass inputs following treatments applications (Pietikainen and
Fritze, 1995; Eivazi and Bayan, 1996; Wang et al., 2012).
Particulate Organic Matter
Particulate organic matter described as organic matter suspended in water is an
important carbon and energy source (Cambardella and Elliott, 1992). Particulate organic
carbon (POC) is a labile fraction component of soil organic carbon (SOC) hence, the
impact of prescribed burn and/or thin on SOC quantity will affect its availability. Forest
management can also result in no change, a decrease or an increase in SOC and
ultimately POC ( Pietikainen & Fritze, 1995; Bird et al., 2000; Johnson and Curtis, 2001;
Andersson et al., 2004; Saarsalmi et al., 2004; Maassen et al., 2006; Giai & Boerner,
2007; Chatterjee et al., 2008; Nave et al., 2010; Wang et al., 2012; Geng et al., 2012;).
Decreased or unaltered SOC following fire may be due to heat effect. Destructive
combustion of organic compounds begins at about 200oC, below that temperature organic
matter is not destroyed (Poff, 1996).
9
Decrease in SOC may be because of volatilization or vegetation removal after
burning and/or thinning (Pietikainen & Fritze, 1995; Bird et al., 2000). Effect of fire on
SOC has also been attributed to time since fire application and the soil sampling depth
(Wang et al., 2012). Nave et al. (2010) observed no change in SOC after harvesting
treatment and inferred that forest floor carbon was more vulnerable to decline following
harvest treatment than mineral soil carbon.
Light Fraction
Light fraction (LF) is described as organic matter with a density less than 2.0 g
cm-3(Gregorich and Janzen, 1996). It is comprised primarily of partially decomposed
organic residues with fast decomposition rates. Chemically it is very close to plant litter
and has appreciable amounts of microbial and microfaunal debris (Spycher et al., 1983;
Janzen et al., 1992; Gregorich and Janzen, 1996; Golchin et al., 1997). The LF accounts
for about 0.1 to 0.3% of total weight in cultivated soils, of which there is about 3 to 10%
in grassland and forest soils (Gregorich and Ellert, 1993).
The LF functions as a short-term reservoir of nutrients and a source of readily
metabolized organic matter (Gregorich and Ellert, 1993). It is enriched in carbon,
phosphorus, and nitrogen, constituting approximately 30-40% of total soil organic carbon
and nitrogen (Gregorich and Ellert, 1993). During nitrogen mineralization, microbes rely
heavily on LF as the energy source and plants rely on it for nutrients (Wander et al.,
1994). During LF decomposition, other products that influence soil aggregate stability
are also released (Six et al., 1998).
10
The LF will first be determined to assess the characteristic and quality of active soil
organic matter before and after fire and thinning disturbance. This is important because
the composition of the LF can be used as an important indicator of soil fertility and
quality index.
Forest management may modify SOC fraction degradation rates by altering
enzyme activities (Chatterjee et al., 2008). Studies of enzymatic activities in soil samples
are useful tools for assessing the functional diversities of soil microbial communities or
soil organic mass turnover (Baldrian, 2009). Measuring enzyme activities in soils has a
long tradition in connection with evaluating soil fertility and quantifying processes in
natural and semi natural ecosystems. This approach may permit evaluation of the status
of changed ecosystems (e.g., by soil pollution, soil management, global change) while
providing insights into the functional diversities of the soil microbial communities. In
fertile soils, heterotrophic microorganisms are supplied with detritus from plants and
other biomass rich in carbon and nutrients that are required for cell maintenance and
growth.
Incapable of directly transporting these large molecules into the cytoplasm, the
heterotrophic microorganisms rely on the activities of a myriad of enzymes that they
synthesize and release into the immediate environment. The extracellular enzymes that
are released can depolymerize organic compounds. The generated soluble low-number
oligomers and monomers that are recognized by cell wall receptors are transported across
the outer membrane into the cell (Burns and Wallenstein, 2011). Soil is an inherently
hostile environment for the extracellular enzymes.
11
As soon as the latter leaves the cells, they are exposed to denaturation, degradation, and
inactivation through both biotic and abiotic mechanisms. This might make the
breakdown of organic macromolecules seem like an impossible task at first glance. It is
conceptually wrong to assume a simple relationship between a single enzyme activity and
microbiological activity in soils.
The need to measure the activities of a large number of enzymes and to combine
these measured activities in a single index has been emphasized to provide information
on soil microbial activities (Nannipieri et al., 2003). However, most of the assays used to
determine soil microbiological activities present the same problem in measuring potential
rather than real activities (Nannipieri et al., 1990). Indeed, assays are generally made at
optimal pH and temperature and at saturating concentration of substrate. Furthermore,
synthetic rather than natural substrates are often used, and soils are incubated as slurry
(Nannipieri et al., 1990). In this study, we assayed six carbohydrate hydrolases to
evaluate the long-term impact of prescribed thinning alone or in combination with
triennial burning.
The enzymes assayed were β-glucosidase, invertase, xylanase, amylase, Nacetyl-glucosaminidase and cellulase. The hydrolysis products of the enzymes are
fundamental sources of energy for microorganisms (Eivazi & Bayan, 1996).
Carbohydrate hydrolases such as cellulase, amylase, xylanase and chitinase are enzyme
systems comprised of multiple enzymes: endo- and exo-enzymes (Deng & Popova,
2011). The endoenzymes undertake endohydrolysis of complex carbohydrates (Deng &
Popova 2011).
12
Ultimately, the released mixtures of di-and oligosaccharides are subsequently hydrolyzed
by exoenzymes into monosaccharide (Deng & Popova 2011).
Cellulase and Beta-glucosidase
In the early 1980s, the only enzyme confirmed to be involved with the cellulose
component of lignocellulosic biomass were those of the “cellulase system” (Platt et al.,
1984). Cellulose, the most abundant polysaccharide compound in the biosphere, is
hydrolyzed by a cellulase system. The system comprises of endocellulase (endo-1, 4-βglucanase [EC 3.2.1.4]) and two exocellulase: namely cellobiosidase (exo-1, 4-βglucanase [EC 3.2.1.91]) and β- glucosidase (Deng et al, 2011). β- glucosidase [EC
3.2.1.21] is also known as gentiobiase, cellobiase, emulsin, elaterase, aryl-β-glucosidase,
β-glucoside glucohydrolase, arbutinase, amygdalinase, p-nitrophenyl β-glucosidase,
primeverosidase, amygdalase, limarase, and salicilinase (Deng & Popova 2011).
β-glucosidase activity is the final step of cellulose degradation. It hydrolyzes the
cellobiose (two glucose units) into monosaccharide compounds (glucose) by cleaving βglucosidic linkages from non-reducing terminal ends (Eivazi and Bayan, 1996; Boerne et
al., 2000; Deng and Popova, 2011). This hydrolysis is important as cellubiose, is an
inhibitor of “cellulase” depolymerizing enzymes (Morais et al., 2004). β-glucosidase the
most predominant enzyme is also involved in hydrolysis of β-D-glucopyranoside and a
broad variety of glycosides (Boerner et al., 2000; Berrin et al., 2003; Acosta- Martinez et
al., 2007). β- glucosidase is also important due to its potential in industrial scale
conversion of cellulose to glucose (Cai et al., 1998).
13
The activity of the enzyme is considered an indicator for biomass turnover because it
exhibits a wide substrate specificity. It hydrolyzes nitrophenyl-β-xylopyranoside,
nitrophenyl-β-D-galactopyranoside, nitrophenyl-α-arabinopyranoside, cellubiose,
lamimaribiose and lactose (Berrin et al., 2003; Zanoelo et al., 2004). Berrin et al. (2003)
reported that the physiological function of β-glucosidase depends on the source and
substrate specificity. Langston et al. (2006) summarized their importance in industrial
processes, environmental processes and pharmacology.
Invertase
Invertase (β-D- fructoguranoside fructohydrolase [EC 3.2.1.26]) catalysis results
in the release of monosaccharide from disaccharide and soluble oligosaccharide (Deng
and Popova, 2011). It cleaves sucrose, one of the most abundant soluble sugars in plants,
releasing glucose and fructose. (Frankenberger and Johanson, 1983; Deng and Popova,
2011). Invertase is partially responsible for the breakdown of plant litter in soils
(Frankenberger and Johanson, 1983). In soils under grasslands, the activity of invertase
may be partly associated with light fraction however, in most soils the activity occurs in
the heavy fraction (Ross, 1983).
N-acetyl-β-D- glucosidase
Chitin is the second most abundant amino polysaccharide found in soils and is
derived from the exoskeletons of invertebrates (insects and arthropods) and fungal
hyphae (Wongkaew and Homkratoke, 2009; Deng & Popova, 2011).
14
It is hydrolyzed by two enzyme systems: Endochitinolytic and exochitinolytic systems
(Brzezinska, 2009; Deng & Popova, 2011). Endochitinolytic also called chitinase or β-1,
4-poly-N-acetylglucosaminidase [EC 3.2.1.14] and exochitinolytic [EC 3.2.1.52] also
called N-acetyl-β-D-glucosaminidase (Deng & Popova, 2011). Chitinase randomly
hydrolyzes 1, 4-β linkages in chitin and chitodextrins, while N-acetyl-β-D
glucosaminidase (NAGase) hydrolyzes the terminal non-reducing end (Deng & Popova,
2011). The products are free N-acetyl glucosamine (NAG) units impregnated with easily
mineralized (low molecular weight) carbon and nitrogen rich compounds (Brzezinska,
2009; Deng & Popova, 2011).
In this study, we assayed the activity of N-acetyl-β-D glucosaminidase (hereafter
referred to as NAGase). Availability of the latter in soils depends on microclimate,
microorganism abundance and other substrate quality and availability (Sinsabaugh et al.,
1992). Chitin is intermediate in its resistance to microbial metabolism and therefore, its
synthesis is only induced when other labile C and N sources are absent. The latter is the
reason why it is more abundant in environments that are poor in nutrients (Hanzlikova &
Jandera, 1993; Brzezinska, 2009).
Xylanase
Xylanase (1, 4-β-D- xylan xylanohydrolase. EC 3.2.1.8) enzyme system is
composed of β-xylanase, β-xylosidase, α-L- arabinofuranosidase, α-glucuronidase,
acetylxylan esterase and hydroxycinnamic acid esterases (Deng and Popova, 2011). The
enzyme is classified under family 10 and 11 of glycosyl hydrolases.
15
It catalyzes endohydrolysis of β-1, 4-xylosidic linkages in hemicellulose, the second most
abundant renewable polysaccharide in nature besides cellulose (Anand et al., 1990;
Kandeler et al., 1999; Hu et al., 2008; Deng and Popova, 2011). The end products of the
hydrolysis are short chains of oligomers, xylobiose and xylose (Deng and Popova, 2011).
Xylose is also called wood sugar or aldopentose (Deng and Popova, 2011). Xylanase is
mainly produced by fungi when readily available compounds are exhausted, (Kandeler et
al., 1999). Its industrial uses include Kraft - pulp bleaching, food baking, and animal
feed preparation (Hu et al., 2008). In the environment, it plays an important part in
materials and energy circulation, fruit maturation, seed germination, and fungus
parasitization (Hu et al., 2008).
Amylase
Amylases system include: endo- and exoamylases that synergistically hydrolyze
starch (Deng and Popova, 2011). Endoamylases also called α-amylases randomly
hydrolyze α-1, 4- glycosidic linkages yielding dextrins, oligosaccharides and
monosaccharides. Exoamylases, which include β and γ-amylase, hydrolyze the same
linkage but only from the non-reducing ends of the chain releasing β-maltose and β-Dglucose (Deng and Popova, 2011). In soils, β-amylase is the most active, and catalyzes
the degradation of the heavy fraction organic material rather than the light fraction
(Ebregt and Boldewijn, 1977; Ross, 1983). The enzymes also exist intracellularly in
plants and can be released into soils during litter formation (Ebregt and Boldewijn, 1977).
Like most enzymes, amylase is primarily of microbial origin, particularly bacteria and
fungi (Ebregt and Boldewijn, 1977).
16
Some amylases are found in acidophilic, alkalophilic and thermoacidophilic environment
(Ebregt and Boldewijn, 1977). Like other extracellular enzymes, amylase activities in
soils have been reported to be inhibited by soil clay minerals (Ross, 1983).
Ross (1983) reported a significant decrease in activity of β-amylase in five clay
minerals (three monominerallic clay fractions from soil and two top soils from tussock
grasslands) in unbuffered aqueous suspension of the clay minerals. The decrease was
partly because of the instability of the enzymes in water and in buffered clay suspensions,
in which adsorption of the enzymes was generally incomplete (Ross, 1983). According
to their results, the influence of clay minerals on inhibition of α-amylase activity was in
the order muscovite < allophane < illite < montmorillonite. In the presence of clay
fractions from soils, the order was muscovite < mica-vermiculite < mica-beidellite (Ross,
1983). In soils with high C content, amylase activity has been reported to be higher than
other enzyme activities (Pancholy et a., 1973; Balota et al., 2004). The significance of
enzymes in biotechnology includes its application in food, fermentation, textile and paper
(Mishra and Behera, 2008).
Potential Carbon Mineralized
Soil microorganisms play a dominant role in soil organic matter degradation.
Their respiration is usually limited by bioavailability of organic matter that depends on
chemical and physical availability of the organic matter (Ahn et al., 2009). Chemical
availability is determined by the chemical composition of soil organic matter (SOM).
This the ability of microbial exoenzymes to break organic polymers into smaller units
that can be in dissolved form and passed through microbial cell walls (Ahn et al., 2009).
17
Physical ability refers to the physical location of SOM, if bound within mineral
aggregates or sorbed within small pores (Ahn et al., 2009).
Potential carbon mineralized (PCM) is a measure of the bioavailability of soil
organic matter. There are various methods to quantify PCM but soil incubation is a more
direct approach (Ahn et al., 2009). The carbon mineralized during incubation serves as a
proxy for total PCM (Ahn et al., 2009). Measured carbon mineralization rates have
ranged from less than 0.007 to 35.6% of total soil carbon when varying incubation times
(12-800 days), soil temperature and soil moisture conditions were used (Ahn et al.,
2009).
Assessing the PCM pool is essential in modeling soil carbon dynamics and
ecosystem response to changing environmental factors (Ahn et al., 2009). Management
practices can alter microbial respiration through the short- and long- term effects on soil
physical, chemical, and biological properties (Wang et al., 2012). The practice may alter
soil moisture, nutrient availability and microbial activity (Wang et al., 2012).
Prescribed fire can reduce or increase soil carbon mineralization by altering the
release of labile carbon materials from microbial biomass, and affecting the quality of
substrate needed for microbial growth (Wang et al., 2012). Harvesting or thinning may
increase microbial respiration, decrease mineralization or have no impact at all
(González-Pérez et al.,2004; Maassen et al., 2006; Nave et al.,2010). Potential carbon
mineralized (PCM) was analyzed to assess the general microbial mineralization activity
during organic matter transformation. This was to determine how mineralization was
influenced by various treatments.
18
Dissolved Organic Matter
Dissolved organic matter (DOM) is the organic matter that can pass through 0.45micrometer filter (Thurman, 1985). Litter layer and the upper, organic-rich mineral
horizons are the main sources of DOM in soils whereas the deeper mineral horizons are
the major sinks (Kalbitz and Kaiser, 2007). Organic compounds released from roots are
also sources of DOM; they include exudates, mucilage and muciges (Kalbitz and Kaiser,
2007). Dissolved organic matter is the most active of all labile organic matter because of
its mobility (Chantigny, 2008). It contributes substantially to terrestrial ecosystem
carbon and nitrogen cycles; it serves as an energy source and a potential source of
nitrogen to heterotrophic microorganisms (Yano et al., 2000).
Biodegradation of the DOM is important in its role in nitrogen cycle than in the
carbon cycle (Qualls and Haines, 1992). That is because it prevents the long-term net
loss of nitrogen from the ecosystem or loss via runoffs and leaching (Qualls and Haines,
1992). Given that most of the reduction in DOC is due to abiotic reactions and not
mineralization, DOC can be a fundamental contributor to the total carbon accumulated
and subsequently soil carbon storage (Kalbitz and Kaiser, 2007). Large accumulation of
DOM in terrestrial ecosystems are possibly due to mineralization and stabilization by
sorption to Fe and Al oxides/ hydroxides and clay minerals or stabilization through (co-)
precipitation by polyvalent cations (Kalbitz and Kaiser, 2007).
Dissolved organic matter constitutes various compounds such as phenols,
hexoses, free amino acids and proteins. The easy degradable carbohydrates (hexose),
protein and amino acids are great sources of carbon and nitrogen.
19
They are assimilated by soil organisms for energy and development purposes. Phenols
are carbohydrates released into the soil following degradation of polyphenolic plant
metabolites such as tannins and lignin (Guggenberger et al., 1989). Phenols have
functions that slightly vary from other carbohydrates. Examples include: (i) binding of
proteins, (ii) metal complexion, (iii) interference with sorption of inorganic anions such
as phosphate, and (iv) exerting allelopathic effects on microorganisms and plants
(Herbert and Bertsch, 1995; Zsolnay, 2003). An increase of up to 85% of dissolved
organic matter components post prescribed burn has been reported by González-Pérez et
al. (2004). The impact of prescribed thin varies depending on time since treatment
application.
The impact of management practices on the quality and quantity of labile carbon
fractions, PCM and enzymes activities are often a foreshadow of future soil organic
carbon dynamics and ultimately nutrient cycling (Wan et al., 2001; Fynn et al., 2003;
Andersson et al., 2004; Acosta-Martinez and Harmel 2006; Chatterjee et al., 2008).
20
CHAPTER 3
MATERIALS AND METHODS
Study Site
The study site was the Bankhead National Forest (BNF) in Northwest Alabama.
The BNF is located on the southern Cumberland Plateau and extends through Lawrence,
Winston, and Franklin counties (34o30’ N, 87o30’ W), covering 73,078 ha (Fig. 1). Soils
at the research sites are classified as Typic Hapludults of the Sipsey series in the USDANCRCS preliminary soil map of Lawrence County (Nobles et al., 2009). Such soils are
fine-loamy, siliceous, semi active, thermic Typic Hapludults (Nobles et al., 2009).
The native vegetation at the BNF consists predominantly of oak and oak-pine
woodlands. The predominant pine species include Virginia (Pinus virginiana Mill.) and
loblolly (Pinus teada L.) pines. Predominant oak species include scarlet (Quercus
coccineacata Michx.), black (Quercus velutina Lam.), and white (Quercus alba L.) oaks
(Gaines & Creed, 2003). The average annual temperature is 13oC, with the highest
temperatures occurring between June and August and the lowest between November and
February (Nobles et al., 2007).
21
Precipitation averages 147 cm yr-1 with a udic soil moisture regime; the highest
precipitation occurs between September and February while low precipitation occurs
between March and August (Nobles et al., 2007).
Fig. 1. Map of the Bankhead National Forest showing treatment stands.
22
Experiment Design
The experimental design for the forest soil study was a two-factor, randomized
complete block design. There were 9 treatments each replicated four times. A total of 36
sample units in four blocks. The treatments comprised of three burning patterns (no burn,
every 3- year burn and every 9-year burn cycles) and three levels of thinning (no thin,
thin to 17.22 m2 ha-1 [75ft2 acre-1] basal area, and to 11.46 m2 ha-1 [50ft2 acre-1] basal
area) (Table 1).
Table 1. Treatment applications at the Bankhead National Forest.
Treatment Number
Treatment code
Application
1
T1
Control, No Burn, No Thin
2
T2
9 Year Burn, No Thin
3
T3
3 Year Burn, No Thin
4
T4
No Burn + Heavy Thin†
5
T5
No Burn + Light Thin*
6
T6
3 Year Burn + Heavy Thin†
7
T7
3 Year Burn + Light Thin*
8
T8
9 Year Burn + Heavy Thin†
9
T9
9 Year Burn + Light Thin*
†Heavily thinned sites to 11.46 m2 ha-1 (50 ft2 acre-1)
*Lightly thinned sites to 17.22 m2 ha-1 (75 ft2 acre-1)
This study was carried out on block one because at the time of soil sampling
block one had received 3 cycles of triennial burns (every 3 years burn).
23
In addition, data obtained from the plots subjected to the novennial burns (every 9-years
burn) were excluded. The plots were 9-year burn (T2), 9 year burn + heavy thin (T8),
and 9 year burn + light thin (T9) plots. The triennial burn treatments were performed by
the BNF staff in winter. First application was in 2005, second application in 2009 and
third application in 2012. The nature of the prescribed fire combined with winter burns
resulted in low intensity and severity burn, surface temperatures during fire ranged
between 149o C and 204o C (Nobles et al., 2009). The thinning treatments were carried
out by privately owned companies in August and September of 2005 (Table 1).
Thinning was implemented to release native hardwood species such as oak by
removing competing loblolly pine species (Nobles et al., 2009). Cut pine trees were
skidded to a landing at the edge of the treatment area, where treetops and branches were
removed (Nobles et al., 2009). The bulk of the thinning slash was accumulated in the
landing areas however, small residual amounts of slash produced during harvesting and
tree removal processes were left in situ (Nobles et al., 2009). The reference site, located
at the Sipsey Wilderness area, had been converted to loblolly pines in the 1960s and has
not received any burn or thinning treatment since the conversion (Nobles et al., 2009).
Soil Sampling and Analysis
The upper soil layer is the most influenced by burning and thinning and contains
the highest composition of microbial biomass, microbial activity and labile carbon (Wan
et al., 2001).
24
Soils used in this study were collected in October of 2012, with an auger (10 cm i.d.),
from the 0 to 10 cm depth in three replicates after removing the residue from the soil
surface. The soils were air-dried, ground, and passed through a 2 mm sieve and stored in
plastic bags until used. Soil pH was measured in water at a soil to solution ratio of 1:2,
and the filtered extract was used for electrical conductivity (EC) measurements, using an
Orion conductivity meter (model 160). The pH and EC reported were temperature
compensated at 25oC. Total C, N and S in the soil were determined by dry combustion
method using a vario Max CNS analyzer (Elementar Analysensysteme GmbH).
Inorganic NH4+ and NO3- content of the soil were determined using an
ammonium-nitrate analyzer (Timberline instrument, model no. TL-2800). Elemental
content (P, Mg, K, Na, Ca, Fe, Cu, Zn, Mn) were assessed using an inductive coupled
plasma (ICP) analyzer. Cation exchange capacity (CEC) was determined using the
summation method whereas percent base saturation was determined by dividing the
summation of the total number of cations by the CEC and multiplying the result by 100.
Objective 1: Determine the Effect of Prescribed Burning and Thinning on Labile
Organic Carbon Fractions
Measurement of biologically active carbon fractions, such as light fraction carbon
(LFC), particulate organic carbon (POC), microbial biomass carbon (MBC) and dissolved
organic matter (DOM) reflects changes in soil quality and productivity. These fractions
provide an assessment of soil carbon changes induced by management practices, such as
burning and thinning.
25
The LFC was isolated by flotation in a dense liquid (Gregorich and Janzen, 1996).
Procedure used was the one described by Ding et al. (2002). In brief, approximately 25 g
of air-dried soil was weighed into 250 mL centrifuge bottles, and 70 mL of NaI solution
(1.7 g mL-1) was added. The mixture was shaken for 1 hr to release LF entrapped within
aggregates and centrifuged at 1000 rpm for 15 min (Gregorich and Janzen, 1996). The
suspended material was then filtered under suction using a 0.2 μm filter paper. The LF
material retained on the filter paper was rinsed with 100 mL of a 0.5 M CaCl2 and 0.5 M
MgCl2 followed by a final rinse with 200 mL of deionized water. Rinsing of the LF with
CaCl2 and MgCl2 was done to prevent any remnant biological toxicity, because of sodium
saturation of the ion-exchange sites in the LF (Ding et al., 2002).
The filter paper containing the LF was transferred into a drying pan placed in an
oven and dried at 70oC for 24 hr. After 24 hr of drying, the LF was measured and then
stored in a desiccator until analyzed. The LF was analyzed for total C, N, and S using the
vario max CNS analyzer (Elementar Analysensysteme GmbH). There are two main
reasons for using a solution with density 1.7 g mL-1 twofold. (i) It allows the use of less
toxic inorganic media, which offers advantages of safety and convenience over organic
solvents. (ii) Contamination of the LF with mineral and organo-mineral materials is
prevented.
The POC was determined by dispersing 10 g soil with 30 mL of 5 g L-1 sodium
hexametaphosphate for 16 hrs and the solution filtered through 0.05 mm sieve
(Cambardella and Elliott, 1992). The particles and solution that passed through the filter
were dried at 50oC for 4 days and organic C concentration determined using CNS
analyzer (Elementar Analysensysteme GmbH).
26
Microbial biomass carbon (MBC) was determined on a 15-g oven-dry basis
according to the chloroform fumigation extraction method. A method used to quantify
the total MBC from cells vulnerable to lysis by chloroform (Horwath and Paul, 1994).
In brief, a 50 mL beaker containing 20 g of fresh soil and another beaker containing 30
mL chloroform and boiling chips were placed in a desiccator. The desiccator was
evacuated by attaching it to vacuum until the chloroform started to boil. The vacuum was
stopped and the desiccators vented slowly. The procedure was repeated three times and
the fourth time the desiccator was not vented. The desiccator was sealed off and stored in
the dark for 24 hrs. The procedure was repeated for the control samples except no
chloroform was used.
The desiccators were evacuated after 24 hours to ensure all chloroform fumes had
been removed. Subsequently, fresh soil of approximately 0.2 g was added to each sample
and mixed thoroughly. Each sample was then transferred into a French bottle and an
uncovered vial containing 20 mL of 1M NaOH was placed in each French bottle. The
French bottles were tightly sealed and incubated at room temperature (25oC) for 10 days.
On the 11th day, the vials containing NaOH were removed from the bottles and MBC
determined by measuring CO2 absorbed in NaOH. That was done by back titrating
NaOH with 2 M BaCl2 and 1 M HCl.
27
Objective 2: Study the Impact of Prescribed Burning and Thinning on
Carbohydrate Hydrolases Activities.
Artificial substrates were used for all enzyme assays because of the limited
solubility of the native substrates (Deng and Popova, 2011). All substrates used were
purchased from Sigma Aldrich (Sigma-Aldrich INC Saint Louis MO USA)
β- glucosidase and N-Acetyl-β- glucosaminidase (NAGase) activity
The activity of β- glucosidase was analyzed using a method described by Eivazi
and Tabatabai (1988). The reagents were prepared as follows.
Stock solution of modified universal buffer (MUB). The solution was prepared by mixing
12.1 g of Tris (hydroxymethyl) aminomethane (THAM), 11.6g of maleic acid, 14.0g
citric acid, and 6.3g of boric acid (H3BO3) in about 800 mL of 0.5 M sodium hydroxide
(NaOH). The solution was adjusted to 1 L with 0.5M NaOH and stored under 4oC.
Modified universal buffer (pH 6.0). A 200 mL MUB stock solution was titrated with HCl
(0.5M) to a pH of 6.0 and the volume adjusted to 1L with Deionized water.
p-Nitrophenol-β- D-glucosidase (PNG) (50 mM). This solution was prepared by
dissolving 0.753 g of PNG (sigma-Aldrich, St. Louis, MO, USA) in about 40 mL of
MUB pH 6.0 and adjusted to 50 mL with the same buffer. The solution was stored under
4oC until used.
Calcium chloride (CaCl2) (0.5 M). An amount of 73.5 g of CaCl2.2H2O was dissolved in
deionized water and the final volume adjusted to 1 L.
28
Tris (hydroxymethyl) aminomethane (THAM) buffer (100 mM, pH 12). A 12.1g of
THAM was dissolved in 800 ml of deionized water. The pH was adjusted to 12 by
titration with 0.5 M NaOH and the volume adjusted to 1 L with deionized water.
Standard p-nitrophenol solution (10 mM). An amount of 1.391 g of p-nitrophenol was
dissolved in 800 mL of deionized water and the solution adjusted to 1 L. The solution
was stored in the dark at 4oC until used.
Procedure. Briefly, for each soil sample, 1g of soil was weighed into an Erlenmeyer
flask and mixed with 0.2 mL of toluene. The soil was left to sit under a fume hood for 15
minutes. Subsequently, 4 mL MUB (pH 6) solution and 1 mL of PNG solution were
added to the soil. The flask was covered with a rubber stopper, the soil suspension mixed
thoroughly and incubated at 37oC for an hour. After incubation, 1 mL of 0.5 M CaCl2
solution and 4 mL of 0.1M THAM buffer was added to the soil suspension. The solution
was mixed thoroughly and then filtered using Whatman paper No. 42. The yellow color
intensity of the filtrate was measured using a spectrometer at 405 nm. The amount of pnitrophenol released was calculated by reference to a calibration curve developed with
standards containing 0, 100, 200, 300, 400, and 500 nmol of p- nitrophenol.
The procedure for the controls was similar to the samples except the substrate was
added after termination of the reaction using THAM buffer (pH 12). The procedure for
analyzing N-acetyl-β- glucosaminidase (NAGase) was similar to the one described in βglucosidase assay with exception of the substrate and buffer used. The substrate used
was ρ- nitrophenyl- N- acetyl-β-D-glucopyanoside; acetate buffer (100 mM, pH 5.5) was
used in place of MUB (pH 6.0).
29
Invertase, cellulase, amylase and xylanase activities
Analysis of the activities of invertase, cellulase, amylase, and xylanase was
carried out according to the procedure described by Deng and Tabatabai (1994). The
protocol used involved the release of reducing sugars after hydrolysis of artificial
substrates. The substrates were 10% sucrose (invertase), 2% carboxymethyl cellulose
(cellulose), 2% starch (amylase), 1.2% xylan (xylanase) and 1.5% chitin (chitinase).
A gram (1 g) of soil was weighed and mixed with 0.2 mL toluene in a 50 ml
Erlenmeyer flask. The flask was placed under a fume hood for 15 minutes after which 20
mL of the respective substrate solution was added. A rubber stopper was used to cap the
flask and the solution mixed thoroughly before incubating for 24 hrs at 30oC. The
solution was mixed thoroughly once again following incubation then transferred into a
centrifuge tube and centrifuged at 17,000g for ten minutes at 4oC. The supernatant was
filtered through a Whatman paper No.42 and the filtrates used for quantification of
reducing sugars. Quantification of the released reducing sugar in soil extract was
performed using the Somogyi-Nelson colorimetric method as described by Deng and
Tabatabai (1994). Reagents were prepared as follows.
K- Saturated cation- exchange resin. This resin was prepared by adding 1M KCl to
analytical grade cation exchange resin (AG 50W-X8, 20 to 50 mesh, hydrogen form) then
shaking the mixture for 15 minutes (Sigma-Aldrich INC Saint Louis MO USA. 44504100G). The KCl solution was decanted and the procedure repeated two more times
before washing thoroughly with distilled water.
30
Used resin was regenerated by washing the resin with three-column volume of NaOH,
five column volume of DI water, three column volume of HCl, five column volume of
distilled water, three column volume of KCl and then finally ten column volume of
distilled water.
Somogyi reagent 1. This was prepared by dissolving 30 g of anhydrous sodium
carbonate (Na2CO3), 19.755 g of sodium potassium tartrate (C4H4KNaO6.4H2O), and 180
g of anhydrous Sodium Sulfate (Na2SO4) in 800 mL of boiled DI water. After the salts
dissolved, the volume was adjusted to 1 L using distilled water. Solution was stored at
room temperature until used.
Somogyi reagent 2. This was prepared by dissolving 45g of anhydrous Na2SO4 and 5 g
of Cupric sulfate (CuSO4. 5H2O) in 200 mL of boiled distilled water. The solution was
adjusted to 250 mL with distilled water and stored at room temperature until used.
Nelson reagent. This was prepared by dissolving 25 g of ammonium molybdate
(NH4)6Mo7O24.4H2O) in 450 ml of distilled water, dissolving 3 g of sodium arsenate
(Na2HAsO4.7H2O) in 25 mL distilled water then adding this solution and 21 mL of
concentrated sulfuric acid (H2SO4) into the ammonium molybdate solution. Acid was
added into 450 mL solution first then 25 mL solution was added second to prevent the
solution mixture from becoming cloudy, the latter interferes with absorbance readings.
The solutions mixture was then stirred in a 55oC water bath for 25 minutes after which it
was poured and stored in a brown bottle covered with foil paper. After cooling, a rubber
stopper was placed on the brown bottle.
Glucose standard solution (5.0 mM). This was prepared by dissolving 0.009 g of glucose
in 1 L of distilled water. The solution was stored in a cooler at 4oC.
31
Procedure. An aliquot of the filtrate (about 10 mL) was transferred into centrifuge tubes
containing 3 g of K- saturated cation exchange resin. The solution was shaken
vigorously for 30 minutes, and then 1 mL of each sample solution transferred into a 15
mL test tube and adjusted to 6 mL with DI water. A 2 mL freshly prepared Somogyi 1
and 2 (4:1v/v) reagent solution was added to the test tube solution and mixed thoroughly.
The test tubes were heated in boiling water bath for 20 minutes then cooled to room
temperature. A 2 mL solution of Nelson reagent was added and mixed thoroughly, the
mixture allowed to stand for 45 minutes in order for the color (green) to develop and
stabilize. The color absorbance was read at 710 nm using a Genesys 10 UVspectrometer.
Dilutions were made for all samples that have absorbance values exceeding the 300 nM
glucose standard.
The 300 nM glucose standard was prepared by constructing a calibration curve.
Glucose standard (5.0 mM) solution of the amount 1 mL was diluted with acetate buffer
to 100 mL in a volumetric flask to yield 50 nmol glucose mL-1. Aliquots of the amount 0,
1, 2, 3, 4, 5, and 6 mL were transferred into 15 mL volumetric flasks and volumes
adjusted to 6 mL using DI water. The absorbance readings were used to construct a
calibration curve.
Controls for all enzymes were analyzed with the same procedure except the
substrates were excluded. The controls correct for the background reducing sugars
present in the soil and those generated from the native substrates of the enzyme reaction
(Deng and Popova, 2011). The reducing sugars quantified are those released after the
artificial substrates have been hydrolyzed. The reducing sugars quantification results
were used to calculate enzyme activity.
32
Objective 3: Evaluate the Effect of Prescribed Burning and Thinning on Potential
Carbon Mineralization and Components of Dissolved Organic Matter
Potential carbon mineralization
There are various methods for quantifying PCM but soil incubation is a more
direct approach for the quantification of PCM ((Ahn et al., 2009). The carbon
mineralized during incubation serves as a proxy for total PCM (Ahn et al., 2009).
The potential carbon mineralization (PCM) was determined using a modified method by
Haney et al. (2004). In brief, 10 g of soil was moistened with water to bring the soil to
field capacity. The soil was placed in French bottles containing beakers with 20 ml of 1
M NaOH to trap evolved CO2. Soil was incubated in the bottles at 25oC for 10 d. On the
10th day, the vials containing NaOH were removed from the bottles. PCM was
determined by measuring CO2 absorbed in NaOH. That was done by back titrating
NaOH with 2 M BaCl2 and 0.1 M HCl.
Component of dissolved organic matter
The constituents of dissolved organic matter: phenols, hexoses, amino acids and
proteins were analyzed using the method described by Chantigny et al. (2008). Water extractable organic matter was used in assessing phenol, hexose, protein and amino acid
concentrations in soil. The extraction was done by preparing a homogeneous slurry
mixture of 5 g of moist soil and 10 mL of 5 mM CaCl2 solution in a 50 mL centrifuge
tube. The solution was centrifuged at 12,000 g for 10 minutes to reduce clogging during
filtration.
33
The supernatant was filtered through a vacuum filter unit with a 0.4µm- polycarbonate
filter then the filtrate transferred in a glass vial and stored at 4oC until analyzed.
Determination of phenol. Reagents and solutions were prepared as follows. A saturated
Na2CO3 solution was prepared by dissolving 216 g in 1 L of deionized water. Stock
standard solution was prepared by dissolving 100 mg of 2-hydrobenzoic acid in a liter of
deionized water. Working standards 2.5, 5, 10, 20, 30 and 40 mg L-1 of diluted 2hydrobenzoic acid were prepared from stock solution dilution.
The procedure used to determine phenol concentration is as follows. A 0.7 mL of
the water extractable dissolved organic matter was mixed with 50 µL of folin-Ciocalteu`s
reagent in a 1.5 mL Eppendorf tube and left to stand for 3 minutes at room temperature.
A 100 µL of saturated Na2CO3 solution and 150 µL of deionized water were added to the
solution and mixed thoroughly. In case of a precipitate formation, the solution was
centrifuged for 2-3 minutes at 2000 g and absorbance read immediately. Absorbance was
read at 725 nm against a blank. Samples developed a blue color when phenols were
present. The blank was colorless.
A calibration curve was prepared and phenol concentration calculated in mg L-1 2hydroxybenzoic acid equivalent. The standard solution was prepared with the same
procedure as the one described for sample solution. A blank was prepared following the
same procedure as sample but deionized water was used in place of the extracted
dissolved organic matter.
Determination of hexoses. Reagents and solutions used were prepared as follows.
Anthrone- sulfuric acid reagent was prepared by dissolving 0.2 g of anthrone (analytical
grade) in 100 mL of concentrated sulfuric acid.
34
The solution was left to stand for an hour at room temperature before use. It was also
prepared fresh every day. Stock standard solution was prepared by dissolving 100 mg of
glucose in a liter of deionized water. Working standards 2.5, 5, 10, 20, 30 and 50 mg L-1
of diluted glucose were prepared from stock solution.
The procedure used to quantify hexose was as follows. A 1mL of extracted
dissolved organic matter sample solution was mixed with 2 mL of anthrone-sulfuric acid
reagent. The solution was vortexed and left to stand for 15 minutes at room temperature.
A sufficient amount of standard or anthrone-treated sample was transferred to a glass
cuvette and the absorbance read at 625 nm against the blank. A calibration curve was
prepared and phenol concentration calculated in mg L-1 glucose equivalent. The standard
solution was prepared using the same procedure as the one described for sample solution.
A blank of the same volume as the sample was used.
Determination of free amino acids. Reagents and solutions were prepared as follows.
Acetate buffer (pH 5.5) was prepared by dissolving 54 g of Na acetate trihydrate in 40mL
of deionized water then adding 10 mL of glacial acetic acid. The pH of the solution was
adjusted to 5.5 with NaOH. Ninhydrin reagent prepared by dissolving 2 g of ninhydrin
and 0.3 g of hidrindantin in 75 mL of 2-hydroxy ethanol. The solution was purged with
N2 for 30 min after which 25 mL of acetate buffer (pH5.5) was added. Solution was
prepared fresh daily with limited air exposure. The dilutant was prepared by mixing
equal amounts of 95% ethanol and deionized water. Stock standard solution was
prepared by mixing 1000 µmol leucine solution in a liter of deionized water. Working
Standards 20, 40, 60, 80 and 100 µmol L-1 of diluted 2-hydrobenzoic acid were prepared
by diluting the stock solution
35
Amino acid concentration in soil was determined according to the ensuing
procedure. Dissolved organic matter sample solution of the amount 2 mL was mixed
with 1.25 mL of the ninhydrin reagent in 10 mL glass tubes. The tubes were capped with
Teflon-lined screw caps and kept in 95oC water bath for 25 minutes. The tubes were
cooled to room temperature in another water bath, and then 4.5 mL of dilutant was mixed
with the cooled solution. A sufficient amount of standard or treated sample was
transferred to a glass cuvette and absorbance read at 570 nm against a blank.
A calibration curve was prepared and amino acid concentration calculated in µmol L-1
leucine equivalent. The standard solution was prepared with the same procedure as the
one described for sample solution. Deionized water of the same volume as sample was
used as a blank.
Protein. Three reagents and solutions used in the analysis were prepared as follows.
Stock standard solution was prepared daily by dissolving 100 mg of bovine serum
albumin (BSA) in a liter of deionized water. Working standards 2.5, 5, 10, 15, 20 and 25
mg L-1 of diluted BSA were prepared by diluting the stock solution. The purchased
Bradford protein reagent was stored in refrigerator until used
Subsequently, protein was quantified as follows. Bradford protein reagent of the
amount 0.5mL was added into a spectrophotometer cuvette and mixed with 0.5ml of
dissolved organic matter sample solution, standard solution or blank solution. The
mixture was left to stand for 5 minutes at room temperature then absorbance read at 620
nm against the blank. A calibration curve was prepared and protein concentration
calculated in mg L-1 BSA equivalent.
36
Statistical Analysis
Analysis of variance (ANOVA) followed by a turkey test were performed using
SAS statistical package software version 9.3 (SAS Institute INC, Cary, NC). The
analysis was performed to detect treatment differences on various organic carbon
fractions, enzymes activities, and components of dissolved organic matter. Results were
considered significant at P < 0.05.
A Correlation analysis was also performed using SPSS software to determine
whether there was a significant correlation between carbon fractions, enzymes activities,
dissolved organic matter components and the physical properties of soil. Data were log
transformed if not normally distributed before analysis.
37
CHAPTER 4
RESULTS AND DISCUSSION
Results of the soil properties are shown in Table 2a and 2b. The soil was highly
acidic with the pH values ranging from 4.7 ± 0.41 to 5.2 ± 0.52 (Table 2a). Like most
forest soils, the CEC was very low ranging from 1.28 ± 0.41 to 3.05 ± 1.75 cmol kg-1 soil
(Table 2a). Base saturation was also low, the highest value was 81.0 ± 12.7 and the least
value 48.5 ±27.2 (Table 2a). The low pH is an indication of high concentrations of
aluminum and hydrogen in soil, which could explain the low base saturation. Soil
moisture was also minimal with a high moisture content of 27.2 ± 4.9 and a low of 17.8 ±
8.3 percent (Table 2a).
Conductivity was low, the highest conductivity observed was in plots treated with
a combination of thin and burn; heavy thin + burn and light thin + burn plots (92.1 ± 20.2
and 105.5 ± 14.0 µs cm-1). The reference plot had the least conductivity at 42.07 ± 2.3 µs
cm-1 (Table 2a). The available iron (Fe) concentration was very high compared to copper
(Cu) and Zinc (Zn) content as expected in this low pH soils. Available phosphorus was
very low possibly due to precipitation and adsorption in the acidic soil. It ranged from
3.27 ± 0.35 (T 3) to 5.61 ± 1.1 (T 7) mg kg-1 (Table 2a).
.
38
Table 2a. Soil properties used.
39
Treatment
pH
(H2O)
% moisture
Conductivity
µs cm-1
CEC
cmol Kg-1
% BS†
T1
4.9 ± 0.38
20.8 ± 1.7
42.07 ± 2.3
1.80 ± 0.39
65.7 ± 24.5
0.15 ±0.03
1.9 ± 0.29
77 ± 0 26
4.18 ± 0.84
T3
4.5 ± 0.36
27.2 ± 4.9
61.5 ± 15.3
2.14 ± 0.72
65.7 ± 25.8
0.19 ± 0.09
1.8 ± 0 .07
93 ± 0 25
3.27 ± 0.35
T4
4.7 ± 0.41
22.9 ± 0.5
74.8 ± 24.2
2.76 ± 0.60
81.0 ± 12.7
0.26 ± 0.01
3.8 ± 0 62
72 ± 0 18
5.56 ± 1.6
T5
4.9 ± 0.37
17.8 ± 4.3
66.2 ± 14.2
2.28 ± 1.20
58.1 ± 18.6
0.22 ± 0.1
2.5 ± 1.1
81 ± 0 32
4.21 ± 0.85
T6
5.1 ± 0.48
22.9 ± 4.1
92.1 ± 20.2
1.28 ± 0.41
48.5 ± 27.2
0.22 ± 0.14
1.7 ± 0.38
68 ± 0 23
5.22 ± 1.2
T7
5.2 ± 0.52
21. ± 5.0
105.5 ± 14.0
3.05 ±1.75
77.8 ± 29.3
0.25± 0.01
2.0 ± 0.14
45 ± 0 18
5.61 ± 1.1
Cu
Zn
Fe
P
--------------------mg kg-1 Soil --------------------------
†Base saturation
Values are means ± standard deviations of three samples per treatment.T1, Reference (no burn no thin); T3, Burn only; T4, Heavy
Thin; T5, Light Thin ;T6, Heavy Thin + 3 yr burn; T7, Light Thin + 3 yr burn.
Total nitrogen and carbon content were as high as 0.112 ± 0.06 (T 6), and 2.364 ±
0.99 (T 6), and as low as 0.08 ± 0.01 (T 1), and 1.512 ± 0.91 (T 1) percent (Table 2b).
Their proportions, as indicated by C:N ratio, were between 19.01 ± 1.46 and 23.72 ± 3.03
(Table 2b), a possible reflection of high mineralization rate in these soils. Ammonium
(NH4+) and nitrate (NO3-) concentrations varied. Relative to other plots, light thin + burn
had very high concentrations of NH4+ and NO3-, (19.57 ± 27.5 and 21.72 ± 33.66 g kg-1
soil) respectively (Table 2b). The large standard deviations indicate high level of
variability in this soil.
The Effect of Prescribed Burning and Thinning on Labile Organic Carbon
Fractions in a Forest Ecosystem
Microbial biomass carbon
Microbial biomass carbon (MBC) ranged from 618 ± 318 to 1335 ± 91 g Kg-1
(Fig. 2). Treatments had some effect on MBC however this effect was not statistically
significant (P < 0.05) (Fig. 2). The reference plot had the highest MBC (1335 ± 91 g Kg1
) relative to the other treatment plots (Fig. 2). The heavy thinned and the light thinned +
burn treatments soils had the least MBC content (675 ± 160 and 618 ± 318 g Kg-1)
compared to the light thin, heavy thin + burn and burn only soil (Fig. 2). Microbial
biomass carbon quantity may have been reduced following burn and thin treatments
because of direct or indirect effect.
40
Table 2b. Soil properties used.
Treatment
N
C
S
C:N
NH4+
NO3-
--------------mg kg-1-------------
-----------------------------%-----------------------
41
T1
0.080 ± 0.01
1.512 ± 0.91
0.011 ± 0.003
19.01 ± 1.46
6.467 ± 3.59
3.115±0.128.
T3
0.096 ± 0.04
1.766 ± 0.47
0.012 ± 0.003
19.43 ± 3.88
7.572 ± 2.74
0.00 ± 0.00
T4
0.102 ± 0.01
2.092 ± 0.17
0.012 ± 0.001
20.52 ± 2.48
5.619 ± 1.08
0.015 ± 0.025.
T5
0.094 ± 0.03
2.211 ± 0.65
0.012 ± 0.004
23.72 ± 3.03
4.451 ± 1.45
4.349 ± 2.669.
T6
0.112 ± 0.06
2.364 ± 0.99
0.015 ± 0.006
21.54 ± 1.54
3.031 ± 1.83
0.025. ± 0.043.
T7
0.102 ± 0.05
1.960 ± 0.83
0.012 ± 0.004
19.27 ± 1.18
19.57 ± 27.5
21.72 ± 33.66
Values are means ± standard deviations of three samples per treatment.T1, Reference (no burn no thin); T3, Burn only; T4, Heavy
Thin; T5, Light Thin ;T6, Heavy Thin + 3 yr burn; T7, Light Thin + 3 yr burn.
3000
Reference
Burn
Heavy Thin
Light Thin
Heavy Thin+Burn
Light Thin+Burn
Microbial biomass carbon (g kg-1)
2500
a
2000
1500
1000
a
a
a
a
a
500
0
Treatments
Fig. 2. Microbial biomass carbon content at 0-10 cm soil depth following various
treatment applications at Bankhead National Forest. Bars with the same letters are not
significantly different. The error bars are standard deviation.
Possible direct effects that may have led to MBC reduction include: (i) heat
induced death, (ii) mortality due to toxic compounds produced during combustion, and
(iii) radiation from the sun following plant cover removal by burning or thinning
(Andersson et al., 2004; Williams et al., 2012; González-Pérez et al., 2004).
42
Indirect effects such as variation in temperature, pH, soil moisture, and the
quality/ quantity of substrate may have negatively affected MBC, possibly because of the
exposed soil surface exposure resulting from vegetation removal (Pietikäinen and Fritze,
1995; Thibodeau et al., 2000; Fynn et al., 2003; Andersson et al., 2004; Mahía et al.,
2006; Wang et al., 2012). Microbial biomass carbon may have been even lower in the
burned and thinned plots relative to the control because of temperature variation.
Undisturbed vegetation cover may have provided an insulating layer that may have
maintained a slightly more suitable environment for microbial activity in the reference
plots than in the burned and thinned plots.
Microbial growth in soil is controlled by the quantity of labile carbon available
(Thibodeau et al., 2000). A possible decrease in labile carbon concentration as a result of
reduced organic matter from litter fall or via biomass removal may have negatively
influenced MBC (Wang et al., 2012). Our results were in agreement with other reported
data (Williams et al., 2012; Maassen et al., 2006). The researchers reported no
significant change in soil microbial carbon in infrequently burned sites and no significant
change in soil microbial biomass five years post thinning.
Particulate organic carbon
Figure 3 represents the impact of burning and thinning on particulate organic
carbon (POC) content. The POC content in burned only soil was lower than in the heavy
thin + burn, light thin + burn, light thin and heavy thin. Some studies also reported
decreased soil organic matter after repeated burn applications (Nobles et al., 2009;
Williams et al. 2012).
43
The POC concentration in the burn only treatment (762 ± 223 g Kg-1) however was
slightly more than the reference plot, 667 ± 160 g Kg-1 (Fig. 3). Although POC content
was impacted by treatment application, the impact was not statistically significant (P <
0.05).
2500
Reference
Burn
Heavy Thin
Light Thin
Heavy Thin+Burn
Light Thin +Burn
Particulate Organic carbon (g Kg-1)
2000
a
a
a
1500
a
1000
a
a
500
0
Treatments
Fig.3. Particulate organic carbon content at 0-10 cm soil depth following
various treatment applications at Bankhead National Forest. Bars with the same
letters are not significantly different. The error bars are standard deviation.
44
Given that POC are fractions of soil organic carbon (SOC), altered SOC quantity
may contribute to changes in POC content. Burning causes defoliation, and consequently
reduces organic carbon incorporation in soil (Fynn et al., 2003).
Reduced organic carbon may explain the reduction in POC. Absence of covering
vegetation results in wider variations in soil temperature and moisture (Pietikäinen and
Fritze, 1995). A reduction in vegetation cover following burning may have caused an
increase in temperature and accelerated POC degradation, which may also explain why
POC levels were reduced in the burn treatment more than in other treatments.
Thinning residue represents a source for readily decomposable carbon and
nitrogen (Thibodeau et al., 2000). The positive effects of thinning treatments on POC
levels were still persistent 7 years post thinning as observed in the heavy thin + burn
treatment that had the highest POC content (Fig. 3). Thinning treatment may have also
induced ameliorated effects on soil and enhanced plant growth, subsequently increasing
organic matter input and incorporation in soil. Consequently, POC increased.
Our results were consistent with that of Giai and Boerner (2007). They observed
insignificant change in SOC quantity after repeated burning (every 4 years), in thinned
treatments, and in thin treatments post-burn. Our results were also similar to data
reported by Nave et al. (2010). They found no significant change in SOC following
harvesting. Maassen et al. (2006) and Geng et al. (2012) also observed no significant
change in treatment effect 5 years and 1 year post thinning.
45
Light fraction carbon
Figure 4 shows light fraction (LF) isolated from soils. It is difficult to visually
and physically distinguish the LF from different treatment plots, but chemically, LFC was
significantly (P < 0.05) affected by treatment (Fig. 5). The fraction was 63.26% more in
the light thin treated plot than in the reference plot (Fig. 5). Harvesting may change soil
organic carbon balance by altering climatic conditions such as temperature and moisture
that drive plant and microbial processes (Maassen et al., 2006).
Fig. 4. Picture of extracted light fraction carbon from soil. This fraction
was isolated using NaI solution of density 1.56 g/cc
Immediately post light thin treatment in 2005, incorporation of charred wood and
herbaceous residue may have increased LFC composition (Nobles et al., 2009) in the
treatment plots than the reference plot.
46
Light fraction carbon may have remained elevated 7 years later due to enhanced plant
growth that continue to supply organic matter through fallen leaves and dead wood. Burn
alone and heavy thin + burn treatments reduced LFC content more than the light thin and
light thin + burn treatment.
Light fraction carbon concentration (g Kg-1)
1500
a
Reference
Burn
Heavy Thin
Light Thin
Heavy Thin+Burn
Light Thin +Burn
1000
ab
ab
ab
ab
500
b
0
Treatments
Fig. 5. Light fraction carbon content at 0-10 cm soil depth following various
treatment applications at Bankhead National Forest. Bars with the same letters
are not significantly different. The error bars are standard deviation.
47
Heavy thin may have generated more fuel for fire thus organic matter combustion
was probably more. That may explain why heavy thin + burn treatment had the least
LFC composition (Fig. 5). The LFC in the light thin treatment was statistically different
from the control but not from the other treatment. The impact of treatment on the LFC
was in the order of light thin > heavy thin > light thin + burn > burn only > heavy thin +
burn > reference. Other studies have also reported insignificant change on active carbon
post burn and thinning treatments (Nobles et al., 2009; Maassen et al., 2006). We
inferred that burn and thin treatments positively altered LFC content because the
reference plot had the least LFC content.
The Impact of Prescribed Burning and Thinning on Carbohydrate Hydrolases
Activities in a Forest Ecosystem
Cellulase Activity
Cellulase activity was highest in the reference site relative to the site treated by
burn and thin (Fig. 6). Cellulose composition may have declined post burn and thin
treatments because of organic matter loss via volatilization, oxidation, biomass removal
and reduced litter input (Maasen et al., 2006; Nobles et al., 2009; Geng et al., 2012). In
addition, the acidic nature of the soil, low moisture, and low organic matter quality and
quantity (Tables 2a and 2b) may have contributed substantially to the reduced cellulase
activity. Heavy thin + burn treatment had the greatest impact on cellulose activity
compared to the other treatment (Fig. 6). Despite the high sensitivity of cellulase to
heavy thin + burn treatment, cellulase activity was not significantly different between
treatments.
48
The insignificant difference of cellulase activity between treatments may be due to high
variability (standard deviation) observed among the treatments, especially in burn only
and heavy thin treatment soils (Fig. 6). Thinning intensity is an important factor as it
may induce beneficial or detrimental effects on nutrient cycling, depending on the
quantity of organic matter removed and how much slash is added (Geng,et al., 2012).
Cellulase activity (µmol g-1 soil 24hr-1)
1500
Reference
Burn
Heavy Thin
Light Thin
Heavy Thin+Burn
Light Thin+Burn
a
1000
a
a
a
a
500
a
0
Treatments
Fig.6. Cellulase activity in soil at 0-10 cm soil depth following various
treatment applications at Bankhead National Forest. Bars with the same
letters are not significantly different. The error bars are standard deviations.
49
Heavy thin alone or the post-burn heavy thin treatments may have caused high
organic matter losses and ultimately reduced cellulose and the ensuing cellulase activity.
Availability of organic matter controls decomposition of substrates because organic
matter is a precursor for enzyme synthesis (Bandick and Dick, 1999; Kaiser et al., 2010).
Often the type of organic matter influences cellulase activity more so than the quantity of
organic matter (Bandick and Dick, 1999; Balota et al., 2004).
Beta-glucosidase Activity
Beta-glucosidase activity ranged from 190 and 284 µmol g-1 soil hr-1, with the
least activity in the reference plot and the highest activity in the light thin only plot (Fig
7). Generally, burn and thin treatments stimulated β-glucosidase activity. Due to high
variability within treatments, treatment effect on β-glucosidase was not statistically
significant (P < 0.05). Sites treated with heavy thin only or heavy thin + burn exhibited
the least β-glucosidase activity compared to burn only, light thin only and light thin +
burn sites (Fig. 7).
Studies conducted by Rietl and Jackson (2012) and Eivazi and Bayan (1996)
found a decrease in activities of β-glucosidase following repeated burn (every 6 years).
They attributed the decrease in β-glucosidase activities to a decrease in soil moisture and
soil organic matter content. Our results are consistent with findings by Boerner and
Brinkman (2003) who reported that triennial burns showed no significant change in the
enzymes activity post fire. They concluded that organisms responsible for the production
and activity of β- glucosidase were less susceptible to disruption by fire.
50
Maassen et al. (2006) and Geng et al., (2012) also observed no significant change in βglucosidase activity following thin treatments.
Beta-glucosidase activity (µmol g-1 soil hr -1)
600
a
Reference
Burn
Heavy Thin
Light Thin
Heavy Thin+Burn
Light Thin+Burn
400
a
a
a
a
a
200
0
Treatments
Fig.7. Beta-Glucosidase activity in soil at 0-10 cm soil depth following various
treatment applications at Bankhead National Forest. Bars with the same letters are
not significantly different. The error bars are standard deviations.
51
Invertase Activity
Figure 8 shows the effects of treatments on invertase activity. Invertase activity
was highest in burn only treatment soils and least in heavy thin treatment soils. However,
invertase activity was statistically insignificant (P < 0.05) (Fig. 8) between treatments.
4000
Invertase activity (µmol g-1 soil 24hr-1)
Reference
Burn
Heavy Thin
Light Thin
Heavy Thin+Burn
Light Thin+Burn
3000
a
2000
a
a
a
a
a
1000
0
Treatments
Fig.8. Invertase activity in soil at 0-10 cm soil depth following various
treatment applications at Bankhead National Forest. Bars with the same letters
are not significantly different. The error bars are standard deviations.
52
Invertase cleaves sucrose, one of the most abundant soluble sugars in plants,
releasing glucose and fructose (Frankenberger and Johanson, 1983; Deng and Popova,
2011). The increase in substrate availability may have stimulated the synthesis and
release of invertase in the burn treated plots. Invertase is associated with microorganisms
whose activities have been reported to increase with increased temperature (Mahía et al.,
2006).
Increased temperature during and after burn treatment application may have
stimulated invertase synthesis by microorganisms and the subsequent increased activity.
Vegetation cover may be reduced post fire, and subsequently, the exposed soil surface
may increase in temperature due to the penetrating sun (Poff, 1996). That may cause the
proliferation of invertase producing organisms.
N-Acetyl-β- glucosaminidase Activity
N-Acetyl-β- glucosaminidase (NAGase) activity was highest in heavy thin and
light thin treatments, 248.28 ± 73.66 and 242.73 ± 152.54 µmol g-1 hr-1 respectively (Fig
9). Relative to other treatments, the combined treatment of heavy thin + burn had the
least influence on NAGase activity (Fig. 9). NAGase is one of the enzymes involved in
the breakdown of chitin, a cell wall component of both fungi and arthropods (Boerner et
al., 2006). Its activity depends on temperature and the type of chitinous substrate hence,
they are more abundant in nutrient impoverished environments and areas with reduced
labile carbon and nitrogen availability (Boerner et al., 2006; Brzezinska et al., 2009).
Vegetation removal and reduced organic matter input post thinning + burning may have
caused a tremendous decrease in nutrient and labile carbon, resulting to high activity.
53
Our results do not support the findings of Rietl and Jackson ( 2012) and Eivazi and
Bayan (1996) who observed a decreases in NAGase activity following repeated burn
(every 6 years). Treatment application did not affect NAGase activity significantly.
Similar findings had been reported by Giai & Boerner, (2007) following repeated burn
(every 4 years) and thin applications.
600
NAGase activity (µmol g-1 soil hr-1)
Reference
Burn
Heavy Thin
Light Thin
Heavy Thin+Burn
Light Thin +Burn
a
400
a
a
a
a
a
200
0
Treatments
Fig. 9. NAGase activity in soil at 0-10 cm soil depth following various
treatment applications at Bankhead National Forest. Bars with the same letters
are not significantly different. The error bars are standard deviations.
54
Xylanase Activity
Xylanase activity was highest in the reference (no burn, no thin) plot compared to
all other treatments (Fig. 10). Substrates may be lost via oxidation during burning or lost
after thinning due to biomass export and reduced organic matter inputs.
8000
Reference
Burn
Heavy Thin
Light Thin
Heavy Thin+Burn
Light Thin+Burn
Xylanase activity (µmol g-1 soil 24hr-1)
a
6000
a
a
a
4000
a
a
2000
0
Treatments
Fig. 10. Xylanase activity in soil at 0-10 cm soil depth following
various treatment applications at Bankhead National Forest. Bars with
the same letters are not significantly different. The error bars are
standard deviations.
55
Heavy thin alone or in combination with burn, had a negative impact on xylanase
activity when compared to burn alone and light thin treatment. Possibly because higher
amount of organic matter was lost in the heavy thin + burn treatment. Availability of
labile carbon and nitrogen controls decomposition of substrates (Kaiser et al., 2010 ).
The treatment means ranging from 3244 to 5223 µmol g-1 were statistically insignificant
(P < 0.05) (Fig. 10). Maassen et al. (2006) also reported insignificant change in xylanase
activity following thin treatment.
Amylase Activity
The light thin + burn treatment had a stimulatory effect on amylase activity
relative to the reference (no burn no thin), burn only and heavy thin only treatments (Fig.
11). The amylase activity was significantly higher in light thin + burn treatment
compared to the reference, burn only and heavy thin treatment plots. Statistically the
impact of Light thin + burn treatment on amylase did not differ significantly to that of
light thin and heavy thin + burn treatments. (Fig. 11). The impact of treatment effect on
amylase activity was in the order burn > reference > heavy thin > light thin > heavy thin
+ burn > light thin + burn.
Of all the enzymes assayed, amylase activity responded to treatment effect
significantly. This is not unusual as enzymes have different functions and not all
resources they utilize are likely to change in the same way as a result of treatment (Geng
et al., 2012). The high activity of amylase in light thin + burn treated plot may be
attributed to the incorporation of incompletely burnt plant material in soil.
56
Incompletely burnt material may have introduced more starch into the soil resulting in
high amylase activity in this treatment. The negative impact of heavy thin, burn and
reference treatments on amylase activity could be as a result of deposition of complex
plant material that may have been slow in decomposition.
200
Amylase activity (µmol g-1 soil 24hr-1)
Reference
Burn
Heavy Thin
Light Thin
HeavyThin+Burn
Light Thin+Burn
a
150
ab
100
50
ab
b
b
b
0
Treatments
Fig. 11. Amylase activity in soil at 0-10 cm soil depth following
various treatment applications at Bankhead National Forest. Bars with
the same letters are not significantly different. The error bars are
standard deviations.
57
Other possible explanations are the loss of available starch compounds via
combustion, or direct heat effect on microbes that synthesize the enzyme. Evaluating
multiple enzyme activities shows the different biochemical reactions in soil (Acosta Martinez and Harmel, 2006). Microorganisms are the main source of enzymes in soil
(Acosta -Martinez et al., 2007). Comparing activities of multiple enzymes might provide
a better picture of microbial structure and the changes in several substrate decomposition
processes. The activities of xylanase, cellulase, amylase and invertase were compared as
illustrated in fig. 12.
8000
6000
4000
2000
In
v
as
e
yl
A
m
er
ta
se
se
an
a
X
yl
el
lu
la
se
0
C
enzyme activity (µmol g-1 soil 24hr-1)
Reference
Burn
Heavy Thin
Light Thin
Heavy Thin+Burn
Light Thin+Burn
Enzymes
Fig. 12. A comparison between enzyme activities subjected to various
treatments at Bankhead National Forest. Error bars are standard deviations.
58
Relative to other enzymes, activities of xylanase and invertase were the highest in
all treatments. These observations were expected as both enzymes degrade compounds
that are less complex than cellulose and starch. Invertase degrades sucrose a soluble
sugar in plants and xylanase is involved in hemicellulose degradation (Deng and Popova,
2011; Frankenberger and Johanson, 1983; Anand et al., 1990; Deng and Popova, 2011;
Kandeler et al., 1999; Hu et al., 2008).
The activities of β- glucosidase and NAGase were also compared. β- glucosidase
showed less activity in all treatments (Fig. 13). NAGase activity has been associated
with availability of nitrogen, its activity is highest in areas with low nitrogen availability
(Rietl and Jackson, 2012). The high NAGase activity could be an indication that the sites
are nutrient impoverished. The enzymes’ responses to various treatments were
inconsistent.
Heterogeneity of enzyme response to treatment can be attributed to the fact that
enzyme have different functions and not all resources they utilize will likely change in
the same way following treatment application (Geng, et al., 2012). Altered substrate
availability may favor the growth of certain microbial groups over others due to different
nutrient demands and growth characteristics of specific microbial groups, thereby causing
microbial community shifts. The response of enzymes to heavy thin treatment was
uniform across all enzymes
Correlation analysis was performed to assess the relationship between enzyme
activity and labile carbon fractions. Xylanase and invertase had a significant negative
correlation with amino acid (Table 3). Particulate organic carbon and light fraction
carbon significantly correlated with amylase, β-glucosidase and NAGase (Table 3).
59
600
Enzyme activities (µmol g-1 soil hr-1)
Reference
Burn
Heavy Thin
Light Thin
Heavy Thin+Burn
Light Thin+Burn
400
200
G
lu
co
s
N
A
G
id
as
e
as
e
0
Enzymes
Fig. 13. A comparison between enzyme activities subjected to various
treatments at Bankhead National Forest. Error bars are standard deviations.
This correlation between POC, LFC with amylase, β-glucosidase and
NAGase suggests that these carbon fractions are a key to the activity of these enzymes in
this forest. Availability of nitrogen controls decomposition of substrates and may
stimulate enzyme synthesis and activity (Kaiser et al., 2010). A study conducted by
Badiane et al. (2001) at forest fallows in semi-arid tropical regions showed a significant
positive relationship between organic carbons with β-glucosidase amylase activity.
60
However, Badiane et al. (2001) found no correlation between carbon content with
chitinase and xylanase activity.
Table 3. Correlation analysis between enzyme activities and labile carbon fractions.
MBC
PCM
POC
LFC
Phenol
Hexose
Amino acid
Cellulase
0.264
-0.045
-0.22
-0. 213
-0.143
0.153
-0.28
Xylanase
0.297
-0.227
-0.303
-0.220
-0.393
-0.056
-0.567*
Invertase
0.175
0.151
0.306
0.419
-0.267
0.301
-0.544*
Amylase
-0.095
-0.355
0.477*
0.243
0.083
0.137
-0.055
β-Glucosidase
0.439
0.454
0.633** 0.602**
0.222
0.325
-0.005
NAGase
0.314
0.378
0.491*
0.201
0.163
0.099
0.478*
*, **, ***, Significant at P ≤ 0.05, 0.01, 0.001; MBC, microbial biomass carbon, PCM,
potential carbon mineralized; POC, particulate organic carbon; LFC, light fraction
carbon.
No correlation existed between pH and the enzymes studied (Table 4). The lack
of correlation between enzyme activity and soil pH is not surprising because the pH of
this soil was well below the optimal pH level for the activities of these enzymes.
Similarly, only β-glucosidase and NAGase activity positively corrected with soil
moisture content, total carbon, total nitrogen and total sulfur content (Table 4). The
relationship between the enzymes and soil moisture suggests that the enzymes were
particularly sensitive to changes in moisture content as affected by treatment.
61
Studies conducted by Rietl and Jackson (2012) and Eivazi and Bayan (1996) observed a
decrease in activities of β-glucosidase. The authors attributed the decrease to reduced
soil moisture and soil organic matter nutrient availabilities.
Table 4. Correlation analysis between enzyme activities and soil properties.
pH
% moisture
C:N
N
C
S
NH4+
NO30.005
Cellulase
-0.107 -0.077
0.079
-0.317
-0.256
-0.352
0.014
Xylanase
-0.262 -0.160
0.276
-0.405
-0.304
-0.320
-0.221 -0.16
Invertase
0.114
0.417
0.035
-0.312
0.332
0.304
-0.164 -0.183
Amylase
0.398
-0.099
0.181
0.211
-0.308
0.179
-0.010 -0.163
β-Glucosidase 0.106
0.558*
-0.298 0.746** 0.709** 0.706**
NAGase
-0.055 0.482*
-0.125 0.583*
0.579*
-0.063 -0.111
0. .609** -0.081 -0.133
*, **, ***, Significant at P ≤ 0.05, 0.01, 0.001
The Effect of Prescribed Burning and Thinning on Potential Carbon Mineralization
and Components of Dissolved Organic Matter
Potential carbon mineralized
Potential carbon mineralized was suppressed in the heavy thin + burn and light
thin + burn but increased in the heavy thin, burn only, and light thin plots compared to
the control (Fig. 14). Carbon mineralization is a function of soil microorganisms’
population and type.
62
Thinning may have provided more fuel during the burning process and as a result a more
intense heat may have affected the microorganisms available, thus suggesting why these
treatments had little carbon mineralized.
In addition, reduced forest floor organic matter and vegetation annual litter fall
may be the reason for the low carbon mineralized. Potential carbon mineralize in the
burn only plot was higher than the control suggesting that the fire intensity may not have
been high due to low fuel. As a result the microbial population would not have been
affected as in the case of heavy thin + burn or light thin + burn. More so, fire may
increase carbon mineralization due to the release of labile organic material and nitrogen
availability (Andersson et al., 2004; Wang et al., 2012). Thinning facilitates carbon
mineralization by increasing substrate availability via litter input and by inducing
ameliorated soil properties such as moisture.
Soil incubation is a method used to quantify potential carbon mineralized. The
soil respiration reflects the amount of carbon mineralized and the latter serves as a proxy
for total potential carbon mineralized (Ahn et al., 2009). Perturbations may alter soil
respiration through effects on the physical, chemical and biological properties of soil.
Additionally, reduced soil respiration in the burned + thinned treatments may be
attributed to low moisture (Andersson et al., 2004).
Dissolved organic matter components
Phenol concentration was highest in light thin treatment and least in the burn only
and heavy thin treatment plots (Fig 15). Light thin + burn and heavy thin + burn
treatments also increase the phenol content in soil compared to the control (Fig. 15).
63
500
a
Potential carbon mineralized (g Kg-1)
400
Reference
Burn
Heavy Thin
Light Thin
Heavy Thin+Burn
Light Thin+Burn
a
a
a
300
a
a
200
100
0
Treatments
Fig. 14. Potential carbon mineralized at 0-10cm soil depth following various
treatment applications at Bankhead National Forest. Bars with the same
letters are not significantly different. The error bars are standard deviations.
Bars with the same letters are not significantly different (P < 0.05).
Despite the variation of phenol content between treatments, the variation was not
statistically significant (P < 0.05) (Fig.15). Phenol is a byproduct of tannins and lignin
(Guggenberger et al., 1989) degradation.
64
Reference
Burn
Heavy Thin
Light Thin
HeavyThin+Burn
Light Thin+Burn
a
4
a
a
2
-1
Phenol concentration
(mg L 2-hydroxybenzoic acid equivalent)
6
a
a
a
0
Treatments
Fig.15. Phenol content at 0-10 cm soil depth as impacted by various
treatment applications at Bankhead National Forest. Error bars are
standard deviations. Bars with the same letters are not significantly
different (P < 0.05).
Heavy thin + burn treatment significantly impacted hexose content compared to
light thin and light thin + burn. Although the hexose content in the light thin and light
thin + burn treatment plots were greater than in the reference, burn only and heavy thin
plots, the differences were not statistically significant (Fig. 16). Major sources of
dissolved organic matter are fresh fallen litter, organic matter on the forest floor and root
exudates, all of which contain high concentrations of hexose (Qualls and Haines, 1992;
Kalbitz and Kaiser, 2007).
65
Reference
Burn
Heavy Thin
Light Thin
HeavyThin+Burn
Light Thin+Burn
Hexose concentration
(mg L-1 glucose equivalent)
300
a
a
200
ab
100
ab
ab
b
0
Treatments
Fig.16. Hexose content at 0-10 cm soil depth as impacted by various
treatment applications at Bankhead National Forest. Error bars are
standard deviations. Bars with the same letters are not significantly
different (P < 0.05).
Light thin and light thin + burn had positive effects on hexose possibly because plant
biomass was incorporated in soil (Johnson and Curtis, 2001). Intensive biomass removal
may be detrimental to hexose availability because fresh litter fall and root exudation
plummets. The subsequent burn treatment reduces forest floor organic matter and
depletes hexose concentration even more.
66
Relative to other forms of nitrogen, the quantities of free amino acids in soil are
low (Tisdale et al., 1985). The heavy thin plot had significantly higher amino acid
concentration relative to all other plots (Fig. 17). Increased organic matter accumulation
post heavy thinning may have resulted to increased degradation and the ensuing release
of amino acid compounds.
Reference and burn only treated sites had the least amino acid concentration.
Concentration of amino acid was significantly less by 71.57% and 72.83% in the
reference and burn only plots compared to the heavy thin + burn plot (Fig. 17). The
concentrations of amino acids in light thin and light thin + burn treated plots were not
significantly different (P< 0.05) from heavy thin + burn, reference and burn only
treatments (Fig. 17). Protein content was below detection limit in the treatment plots.
The low protein content and high amino acid content could be an indication of rapid
degradation of protein resulting to release of amino acid derivatives. High amino acid
concentration may also mean that they may be an important substrate for nitrifying
bacteria and a source of NH4+ (Tisdale et al., 1985).
67
6000
Reference
Burn
Heavy Thin
Light Thin
Heavy Thin+Burn
Light Thin+Burn
Amino acid concentration
(umol L-1 Leucine equivalent)
a
4000
2000
b
bc
c
bc
c
0
Treatments
Fig.17. Amino acid content at 0-10 cm soil depth as impacted by
various treatment applications at Bankhead National Forest. Error
bars are standard deviations. Bars with the same letters are not
significantly different (P < 0.05).
68
CONCLUSION
The soils used in this study are very acidic in nature and very poor in nutrient
content. The available Fe concentration was almost 20 times higher than the available P
concentration. The high available Fe concentration was possibly due to low soil pH
because Fe is more readily available at low pH than at high pH. The electrical
conductivity (a measure of the salt content) ranged from 42.07± 2.3μs cm-1 to 105.5
±14.0μs cm-1. The base saturation was less than 90% in this soil.
The labile carbon fraction in this soil, represented as microbial biomass carbon
(MBC), particulate organic carbon (POC) and light fraction carbon (LFC), responded
differently to treatment. The microbial biomass content was higher in the reference plot
than in the other treatment plots. This suggests that burning, thinning and a combination
of burn and thin negatively affected MBC, although this impact was not statistically
significant. The POC had an opposite trend to MBC. Thinning and burning increased
POC content compared to the reference, although the degree of increase between
treatments was not statistically significant. A similar trend was also observed for LFC
except the light thin treatment was significantly different from the control. Cellulase
activity was highly suppress by the heavy thin + burn treatment.
69
β-D-glucosidase activity ranged from 190 to 284 µmol g-1 soil hr-1, with the least
activity in the reference plot and the highest activity in the light thin plot. Generally,
burn and thin treatments stimulated β-glucosidase activity. Increased temperature during
and after burn treatment application may have stimulated invertase producing organisms
thus increasing invertase activity. The impact of Light thin + burn treatment on amylase
activity was statistically significant compared to amylase activity in reference, burn only
and heavy thin treatment plots. Statistically, the impact of Light thin + burn treatment on
amylase did not differ significantly to the effect of light thin and heavy thin + burn
treatments. Relative to other enzymes, xylanase and invertase activities were the highest
in all treatments.
Correlation analysis performed to assess the relationship between enzyme activity
with labile carbon fractions and soil properties revealed that some relationships do exist.
Xylanase and invertase had a significant negative correlation with amino acid.
Particulate organic carbon and light fraction carbon significantly correlated with amylase,
β-glucosidase and NAGase. No correlation existed between pH and the enzymes studied.
The lack of correlation between enzyme activity and soil pH is not surprising because the
pH of this soil was well below the optimal pH level for the activities of these enzymes.
Similarly, only activities of β-glucosidase and NAGase positively corrected with soil
moisture content, total carbon, total nitrogen and total sulfur content.
Carbon mineralization is a function of soil microbial diversity and type of
substrate involved. Potential carbon mineralize in the burn only plot was higher than the
control suggesting that the fire intensity may not have been high due to low fuel.
70
Thus, microbial population would not have been affected as in the case of heavy thin +
burn or light thin + burn potential carbon mineralized was suppressed.
Phenol, a component of dissolved organic matter, ranged from 1.537 to 3.00 mg
L-1 hydroxybenzoic acid equivalent. Relative to other forms of nitrogen, the quantities of
free amino acids in soil are low. The heavy thin plot had a significantly higher amino
acid concentration relative to all other plots. The increased organic matter accumulation
post heavy thinning may have resulted in increased degradation and the ensuing release
of amino acid compounds. Protein content detected in this soil was minimal to none.
The detection of amino acid but not protein content suggests the rapid degradation of any
released protein into the soil.
71
REFERENCES
Acosta-Martinez, V., Cruz, L., Sotomayor- Ramírez, D., & Pérez-Algería, L. (2007).
Enzyme activities as affected by soil properties and land use in tropical
watershed. Applied Soil Ecology, 35, 35-45.
Acosta-Martinez, V., & Harmel, R.D. (2006). Soil microbial communities and enzyme
activities under various poultry litter application rates. Journal of Environmental
Quality, 35, 1309-1318.
Ahn, M.-Y., Zimmerman, A. R., Comerford, N. B., Sickman, J. O., & Grunwald, S.
(2009). Carbon Mineralization and Labile Organic Carbon Pools in the Sandy
Soils of a North Florida Watershed. Ecosystems, 12, 672–685.
Anand, L., Krishnamurthy,S., & Vithayathil, P. J. (1990). Purification and properties of
xylanase from the thermophilic fungus, Humicola lanuginosa (Griffon and
Maublanc) Bunce. Archives of Biochemistry and Biophysics, 276, 546-553.
Andersson, M., Michelsen, A., Jensen, M., & KjØller, A. (2004). Tropical savannah
woodland: effects of experimental fire on soil microorganisms and soil
emission of carbon dioxide. Soil Biology and Biochemistry, 36, 849-858.
Badiane, N. N. Y., Chotte, J., Pate, E., Masse, D., & Rouland, C. (2001). Use of soil
enzyme activities to monitor soil quality in natural and improved fallows in semi
arid tropical regions. Applied Soil Ecology, 18, 229–238.
Baldrian, P. (2009). Microbial enzyme-catalyzed processes in soils and their analysis.
Plant Soil Environment, 55, 370–378.
Balota, E., Kanashiro,M., Filho,A., Andrade, D., & Dick, R. (2004). Soil enzyme
activities under long - term tillage and crop rotation systems in subtropical agro ecosystems. Brazilian Journal of Microbiology, 35, 300 - 306.
Bandick, A.K., & R.P. Dick, R. P. (1999). Field management effects on soil enzyme
activities. Soil Biology and Biochemistry, 31, 1471-1479.
72
Berrin, J-G., Czjzek, M., Kroon, P.A., Mclauchlan,W.R., Puigserver, A.,Williamson, G.,
& Juge, N. (2003). Substrate (aglycone) specificity of human cytosolic βglucosidase. Biochemical Journal, 373, 41-48.
Bird, M.I., Veenendaal, E.M., Moyo,C., Lloyd,J., & Frost, P. (2000). Effect of fire and
soil texture on soil carbon in a sub- humid savanna (Matopos, Zimbabwe).
Geoderma, 94, 71-90.
Boerner, R. E. J., & Brinkman, J. A. (2003). Fire frequency and soil enzyme activity in
southern Ohio oak – hickory forests. Applied Soil Ecology, 23, 137–146.
Boerner, R.J., Decker, K.M., & Sutherland, E. K. (2000). Prescribed burning effects on
soil enzyme activity in a southern Ohio hardwood forest: a landscape- scale
analysis. Soil Biology and Biochemistry.32, 899-908.
Boerner, R. E. J., Waldrop, T. A., & Shelburne, V. B. (2006). Wildfire mitigation
strategies affect soil enzyme activity and soil organic carbon in loblolly pine (
Pinus taeda ) forests. Canadian Journal of Forest Research, 36, 3148–3154.
Bongiovanni, M. D., & Lobartini, J. C. (2006). Particulate organic matter, carbohydrate,
humic acid contents in soil macro- and microaggregates as affected by cultivation.
Geoderma, 136, 660–665.
Brzezinska, M.S., Lalke-Porczyk, E., Donderski, W., & Walczak, M. (2009).
Degradation of chitin in natural environment: role of actinomycetes. Polish
Journal of Ecology, 57,229-238.
Burns, R. G., & Wallenstein, M. D. (2011). Ecology of extracellular enzyme activities
and organic matter degradation in soil: a complex community-driven process. In
R. P. Dick (Ed.), Methods of Soil Enzymology (SSSA Book.). Madison, WI: Soil
Science Society of America, Inc.
Cai, Y.J., Buswell, J. A., & Chang, S. T. (1998). β-Glucsoidase components of the
cellulolytic system of the edible straw mushroom, Volvariella volvacea. Enzyme
and Microbial Technology, 22,122-129.
Cambardella, C.A. & Elliot, T.E. (1992). Particulate soil organic matter changes across
a grass land cultivation sequence. Soil Science Society of America Journal, 56,
777-783.
73
Certini, G. (2005). Effects of fire on properties of forest soils : a review. Oecologia, 143,
1–10.
Chanders, K., Goyal, S., Mundra, C. M., & Kapoor, K. K. (1997). Organic matter,
microbial biomass and enzyme activity of soils under different crop rotations in
the tropics. Biology and Fertility of Soils, 24, 306-310.
Chantigny, M.H., Angers, A. D., Kaiser,k., & Kalbitz, k. (2008). Extraction and
characterization of dissolved organic matter. In M.R. Carter & E.G. Gregorich
(ed.) Soil sampling and methods of analysis 2nd edition pp. 617- 635. Boca
Raton. Florida: Canadian Society of soil science.
Chatterjee, A., Vance, F.G., Pendall, E & Stahl, D. P. (2008). Timber harvesting alters
soil carbon mineralization and microbial community structure in coniferous
forests. Soil biology and biochemistry, 40, 1901 -1907.
Deng, S., & Popova I. (2011). Carbohydrate hydrolases. In R.P. Dick, (ed.).
Methods of soil Enzymology.9 pp.185-207. Madison, WI: Soil Science Society of
America.
Deng, S.p., & Tabatabai, A. M. (1994). Colorimetric determination of reducing sugars in
soils. Soil Biology and Biochemistry, 26, 473-477.
Ding, G., Novak, M. J., Amarasiriwardena, D., Hunt, G. P., & Xing. B. (2002). Soil
organic matter characteristics as affected by tillage management. Soil Science
Society of America Journal, 66, 421 - 429.
Ebregt, A., & Boldewijn, J. (1977). Influence of heavy metals in spruce forest soil on
amylase activity , carbon dioxide evolution from starch and soil respiration. Plant
and Soil, 47, 137–148.
Eivazi, F., & Bayan, M. (1996). Effects of longterm prescribed burning on the activity of
select soil enzymes in an oak-hickory forest. Canadian Journal of Forest Research,
26, 1799– 1804.
Eivazi, F. & Tabatabai, A. M. (1988). Glucosidases and agalactosidase in soil. Soil
Biology and Biochemistry. 20, 601-606.
Frankenberger T.W., & Johanson, B. J. (1983). Factors affecting invertase activity in
soils. Plant and Soil, 74, 313–323.
74
Fynn, R.W.S., Haynes, J. R., & O' Connor, G. T. (2003). Burning causes long-term
changes in soil organic matter content of a South African grassland. Soil Biology
and Biochemistry. 35, 677-687.
Gaines, G., & Creed, J. (2003). Final Environmental Impact Statement: Forest Health and
Restoration Project, National forest in Alabama, Bankhead National Forest.
USDA, (September). Retrieved from
http://www.fs.usda.gov/Internet/FSE_DOCUMENTS/stelprdb5157290.pdf
Garcia-Montiel, D.C., Neill, C., Melillo, J., Thomas, S., Steudler, A. P., & Cerri, C. C.
(2000). Soil phosphorus transformations following forest clearing for pasture in
the Brazilian Amazon. Soil Science Society of America Journal, 64, 1792-1804.
Geng, Y., Dighton, J., & Gray, D. (2012). The effects of thinning and soil disturbance
on enzyme activities under pitch pine soil in New Jersey Pinelands. Applied Soil
Ecology, 62, 1–7.
Giai, C., & Boerner, R. E. J. (2007). Effects of ecological restoration on microbial
activity, microbial functional diversity, and soil organic matter in mixed-oak
forests of southern Ohio, USA. Applied Soil Ecology, 35, 281–290.
Golchin, A., Baldock,A. J., & Oades, M. J. (1997). A model linking organic matter
decomposition, chemistry, and aggregate dynamics. In: R. Lal, J.M. Kimble, R. F.
Follett & B. A. Stewart (eds.), Soil processes and the carbon cycle pp. 245-266.
Boca Raton, FL: Advances in Soil Science.
González-Pérez, J. a, González-Vila, F. J., Almendros, G., & Knicker, H. (2004). The
effect of fire on soil organic matter--a review. Environment International, 30,
855–870.
Gregorich, E.G., & Ellert, H. B. (1993). Light fraction and macroorganic matter in
mineral soils. In: M.R. Carter (ed.) Soil sampling and methods of analysis pp.
397-407. Boca Raton, Fl. Canadian Society of Soil Science.
Gregorich, E.G., & Janzen, H. H. (1996). Storage of carbon in the light fraction and
macroorganic matter. In M.R. Carter, & B.A. Steward (eds.),. Structure and Soil
Organic Matter Storage in agricultural soils pp. 167-190. Boca Raton, FL.
Advances in Soil Science.
Guggenberger, G., Kogel-Knabner, I., Haumaier, L., & Zech, W. (1989). Gel permeation
chromatography of water- soluble organic matter with deionized water as eluent.
II. Spectroscopic and chemical characterization of fractions obtained from an
aqueous litter extract. Science of the Total Environment. 81-82, 447-457.
75
Gutknecht, J. L. M., Henry, H. a. L., & Balser, T. C. (2010). Inter-annual variation in soil
extra-cellular enzyme activity in response to simulated global change and fire
disturbance. Pedobiologia, 53, 283–293.
Hamman, S. T., Burke, I. C., & Knapp, E. E. (2008). Soil nutrients and microbial activity
after early and late season prescribed burns in a Sierra Nevada mixed conifer
forest. Forest Ecology and Management, 256, 367–374.
Haney,R. L., Franzluebbers , J. A., Porter, B. E., Hons, M. F., & Zuberer, A. D. (2004).
Soil carbon and nitrogen mineralization. Soil Science Society of America Journal.
68, 489-492.
Hanzlikova, A., & Jandera. A. (1993). Chitinase and changes of microbial community in
soil. Folia Microbiologica. 38, 159-160.
Herbert, B.E. & Bertsch, M. P. (1995). Characterization of dissolved and colloidal
organic matter in soil solution: a review. In W.W. McFee & J.M. Kelly (eds.),
Carbon forms and functions in forest soils P 63-88. Madison, WI: Soil Science
Society of America .
Horwath, W. R., & Paul, A. E. (1994). Microbial biomass in microbiological and
biochemical properties of soil. In R. Weaver, P. Bottomly, & S. Angle, (eds.)
Methods of soil analysis, part 2. Microbiological and biochemical properties P.
753–772. Madison, WI: Soil Science Society of America.
Hu, Y., Zhang, G., Li, A., Chen, J., & Ma, L. (2008). Cloning and enzymatic
characterization of a xylanase gene from a soil-derived metagenomic library with
an efficient approach. Applied Microbiology and Biotechnology, 80, 823–830.
Hubbard, R.M., Vose, M. J., Clinton, D. B., Elliott, J. K., & Knoepp, D. J. (2004). Stand
restoration burning in oak-pine forests in the southern Appalachianns: Effects
on above- ground biomass and Carbon and nitrogen cycling. Forest Ecology and
Management, 190, 311-321.
Janzen, H.H., Campbell A. C., Brandt, A. S., Lafond, P. G. & Townley-Smith, L. (1992).
Light-fraction organic matter in soils from long-term crop rotations. Soil Science
Society of America Journal, 56: 6, 1799-1806.
Johnson, D. W., & Curtis, P. S. (2001). Effects of forest management on soil C and N
storage: meta analysis. Forest Ecology and Management, 140, 227–238.
76
Kaiser, C., Koranda, M., Kitzler, B., Fuchslueger, L., Schnecker, J., Schweiger, P.,
Rasche, F., Zechmeister - Boltenstern, S., Sessitsch, A., & Richter, A. (2010).
Belowground carbon allocation by trees drives seasonal patterns of axtracellular
enzyme activities by altering microbial community composition in beech forest
soil. New phytologist, 187, 843-858.
Kalbitz, K., & Kaiser, K. (2007). Contribution of dissolved organic matter to carbon
storage in forest mineral soils. Journal of Plant Nutrition and Soil Science, 170,
52–60.
Kandeler, E., Luxhùi, J., Tscherko, D., & Magid, J. (1999). Xylanase , invertase and
protease at the soil - litter interface of a loamy sand. Soil Biology and
Biochemistry, 31, 1171–1179.
Langston, J., Sheehy, N., & Xu, F. (2006). Substrate specificity of Aspergillus oryzae
family 3 β-glucosidase. Biochimica et Biophysica ACTA/ General Subjects, 1764,
972-978.
Maassen, S., Fritze, H., & Wirth, S. (2006). Response of soil microbial biomass,
activities, and community structure at a pine stand in northeastern Germany 5
years after thinning. Canadian Journal of Forest Research, 36, 1427–1434.
Macadam, A.M. (1987). Effects of broadcast slash burning on fuels and soil chemical
properties in the sub-boreal spruce zone of central British Colombia. Canadian
Journal of Forest Research, 17,1577–582.
Mahía, J., Pérez-Ventura, L., Cabaneiro A., & Díaz-Raviña, M. (2006). Soil microbial
biomass under pine forests in the north-western Spain: influence of stand age, site
index and parent material. Forest Systems, 15, 152-159.
McGill, W., Cannon, K., Robertson, J., & Cook, F. (1986). Dynamics of soil microbial
biomass and water - soluble Organic C In Breton L after 50 years of cropping to
two rotations. Canadian Journal of Soil Science, 66, 1–19.
Mishra, S., & Behera, N. (2008). Amylase activity of a starch degrading bacteria isolated
from soil receiving kitchen wastes. African Journal of Biotechnology. 7, 3326–
3331.
Morais, H., Ramos, C., Forgacs, E., Jakab, A., & Cserhati, T. (2004). Enzyme production
of Pleurotus ostreatus evaluated by the three-way principal component analysis.
Engineering in Life Science, 4, 165-170.
77
Nave L.E., Vance, D. E., Swanton, W.C., & Curtis, S. P. (2010). Harvest impacts on soil
carbon in temperate forests. Forest Ecology and Management, 259, 857-866.
Nannipieri, P., Ascher, J., Ceccherini, TM., Landi, L., Pietramellara, G., & Renella, G.
(2003). Microbial diversity and soil functions. European Journal of Soil Science,
54, 655–670.
Nannipieri, P., Grego, S., & Ceccanti, B. (1990). Ecological significance of the biological
activity in soil. In J. M. Bollag & G. Stotzky (eds.), Soil Biochemistry volume 6 pp.
293–355. New York, NY. Marcel Dekker.
Nobles, M.M., jr.Dillion, W., & Mbila, M. (2009). Initial response of soil nutrient pools
to prescribed burning and thinning in a managed forest ecosystem of North
Alabama. Soil Science Society of America Journal, 73, 285-292.
Nsabimana, D., Haynes, R.., & Wallis, F. (2004). Size, activity and catabolic diversity of
the soil microbial biomass as affected by land use. Applied Soil Ecology, 26, 81–
92.
Pancholy, S.K.& Rice, E.L. (1973) Soils enzymes in relation to old fieldsuccession:
amylase, cellulase, invertase, dehydrogenase, and urease. Soil Science Society of
America Journal, 37,47-50.
Pietikainen, J., & Fritze, H. (1995). Clear cutting and prescribed burning in coniferous
forest: comparison of effects on soil fungal and total microbial biomass,
respiration activity and nitrification. Soil Biology and Biochemistry, 27, 101-109.
Platt, M. W., Hadar, Y., & Chet, I. (1984). Fungal activities involved in lignocellulose
degradation by Pleurotus. Applied. Microbiology and Biotechnology, 20, 150154.
Poff, R J. (1996). Effects of silvicultural practices and wildfire on productivity of forest
soils. Sierra Nevada ecosystem project: final report to Congress. Vol. 2.
Qualls, R., & Haines, B. (1992). Biodegradability of Dissolved Organic Matter in Forest
Throughfall, Soil Solution, and Stream Water. Soil Science Society of America
Journal, 56, 578–586.
Rietl, A. J., & Jackson, C. R. (2012). Effects of the ecological restoration practices of
prescribed burning and mechanical thinning on soil microbial enzyme activities
and leaf litter decomposition. Soil Biology and Biochemistry, 50, 47–57.
78
Ross, D. J. (1983). Invertase and amylase activities as influenced by clay minerals, soilclay fractions and topsoils under grassland Soil Biology and Biochemistry, 15:
287-293.
Saarsalmi, A., Mälkönen, E., & Kukkola, M. (2004). Effect of wood ash fertilization on
soil chemical properties and stand nutrient status and growth of some
coniferous stands in Finland. Scandinavian Journal of Forest Research, 19, 217233.
Sinsabaugh, R.L., Antibus, K. R., Linkens, E. A., McClaugherty,A. C., Rayburn,L., &
Weiland, T. (1992). Wood decomposition in a first order watershed: mass loss as
a function of exoenzyme activity. Soil Biology and Biochemistry, 24,743-749.
Six, J., Elliot,T. E., Paustian, K., & Doran, W. J. (1998). Aggregation and soil organic
matter accumulation in cultivated and native grassland soils. Soil Science Society
of America Journal, 62, 1367-1377.
Spycher, G., Sollins, P., & Rose, S. (1983). Carbon and nitrogen in the light fraction of a
forest soil: Vertical distribution and seasonal patterns. Soil Science, 135,79-87.
Thibodeau, L., Raymond, P., Camiré, C., & Munson, A. D. (2000). Impact of
precommercial thinning in balsam fir stands on soil nitrogen dynamics, microbial
biomass, decomposition, and foliar nutrition. Canadian Journal of Forest
Research, 30, 229–238.
Thomas, G.W. (1982). Exchangeable cations. In A.L. page et al., (ed.) Methods of soil
analysis. Part 2. Chemical and microbiological properties pp.159-166. Madison,
WI: American Society of Agronomy and Soil Science Society of America.
Thurman, E. M. (1985). Organic geochemistry of natural waters (Vol 2). Hingham, MA:
Kluwer academic publishers.
Tisdale, S. L., Nelson, W. L., & Beaton, J. D. (1985). Soil fertility and fertilizers (4th ed).
New York, NY: Collier Macmillan Publishers.
Viro, P.J. (1974). Effects of forest fire on soil. In T.T. Kozlowski & C.E. Ahlgren (Eds).
Fire and ecosystems pp. 7-45. New York, NY: Academic press.
Vose, J., Clinton, B., & Swank, W. (1993). Fire, drought, and forest management
influences on pine/ hardwood ecosystem in the southern applachians. In 12th
International Conference on Fire and Forest Meteorology (pp. 232–238). Jekyll
Island, GA: Society of America Foresters.
79
Wade, D. D., & Lundsford, D. J. (1989). A guide for prescribed fire in southern forests.
USDA For. Serv. Southern Region. Tech. Pub. R8-TP11. Aseville, NC.
Wagner, H., & Wolf, D.C. (1998) Carbon transformation and soil organic matter
formation. In D.M. Sylvia et al., (ed.) Principles and applications of soil
microbiology p.218-256. Upper Saddle River, N J: Prentice-Hall.
Wan, S., Hui, D., & Luo, Y. (2001). Fire Effects on Nitrogen pools and dynamics in
terrestrial ecosystem: A meta-analysis. Ecological Applications, 11, 1349-1365.
Wander, M. (2004). Soil Organic Matter Fractions and Their Relevance to Soil Function.
In F. Magdoff & R. Weil, (Eds.), Soil organic matter in sustainable agriculture (pp.
67–102). Boca Raton, Florida: CRC Press LLC.
Wander, M.M., Traina, J. S., Stinner, R. B., & Peters, E. S. (1994). Organic and
conventional management effects on biological active soil organic matter pools.
Soil Science Society of America Journal. 58,1130-1139.
Wang, Q., Zhong, M., & Wang, S. (2012). A meta-analysis on the response of microbial
biomass, dissolved organic matter, respiration, and N mineralization in mineral soil
to fire in forest ecosystems. Forest Ecology and Management, 271, 91–97.
Wongkaew. P., & Homkratoke, T. (2009). Enhancement of soil microbial metabolic
activity in tomato field plots by chitin application. Asian Journal of Food AgroIndustry. (Special Issue) S325- S335.
Williams, R. J., Hallgren, S. W., & Wilson, G. W. T. (2012). Frequency of prescribed
burning in an upland oak forest determines soil and litter properties and alters the
soil microbial community. Forest Ecology and Management, 265, 241–247.
Yang, Y., J. Guo, G. Chen, Y. Yin, R. Gao, and C. Lin. (2009). Effects of forest
conversion on soil labile organic carbon fractions and aggregated stability in
subtropical china. Plant soil 323: 153 -162.
Yang, K., Zhu, J., Zhang, M., Yan, Q., & Sun, O. J. (2010). Soil microbial biomass
carbon and nitrogen in forest ecosystems of Northeast China: a comparison between
natural secondary forest and larch plantation. Journal of Plant Ecology, 3(3), 175–
182.
Yano, Y., Mcdowell, W. H., & Aber, J. D. (2000). Biodegradable dissolved organic
carbon in forest soil solution and effects of chronic nitrogen deposition. Soil Biology
and Biochemistry, 32, 1743–1751.
80
Zanoelo, F.F., M-L. T-M. Polizeli, H. F. Terenzi, and J. A. Jorge. 2004. β-Glucosidase
activity from the thermophilic fungus Scytalidium thermophilum is stimulated by
glucose and xylose. FEMS Microbiol. Letts. 240(2):137-143.
Zsolnay.A. 2003. Dissolved organic matter: artifacts, definition, and functions.
Geoderma 113: 187-209.
81
VITA
Dessy Owiti was born in Nairobi Kenya December 31st 1985. She obtained her B.S. in
Biological Sciences in 2010 from the University of Alabama Huntsville.
She was
admitted in the graduate school at Alabama Agriculture and Mechanical University in
Summer 2012. She joined the Department of Biological and Environmental Science in
Fall 2012 and pursued the Masters degree of Soil and Plant Science.