NITROGEN FERTILIZATION EFFECTS ON LITTER DECOMPOSITION
DYNAMICS AND SOIL CARBON IN AGRICULTURAL SYSTEMS

By
Dur-e-Shahwar Salam

A THESIS
Submitted to
M
Michigan State University
in partial fulfillment of the requirements
r
for the degree of
MASTER OF SCIENCE
Crop and Soil Sciences
2011

ABSTRACT
NITROGEN FERTILIZATION EFFECTS ON LITTER DECOMPOSITION
DYNAMICS AND SOIL CARBON IN AGRICULTURAL SYSTEMS
By
Dur-e-Shahwar Salam
I examined the effects of three N applications (0,134,291 Kg N /ha) on corn (Zea mays) and
wheat (Triticum aestivum) litter decomposition rates, soil and litter enzymes, soil C pools, and
litter chemistry at the W.K. Kellog Biological Station Long-Term Ecological Research (LTER) site.
There were no changes in litter chemistry after decomposition under N fertilization and the
litter decomposition rates did not respond to N fertilization but there was significantly (P =
<0.001) greater mass loss in corn (73% mass loss) than wheat (63% mass loss). Laboratory
incubations indicated that soil C-mineralization significantly declined (P=0.0001) under 291Kg
N/ha in comparison to 0N. There were no significant differences in light fraction (LF) C and N
between treatments receiving 0 and 291 Kg N/ha. The C concentration (mg/g of LF) of the LF
organic matter increased by 8% in June and 1.6% in Aug in the high N treatment in comparison
to 0N, and the N concentration (mg/g of LF) increased by 16 % in June and by 8% in Aug under
291 Kg N/ha treatment in comparison to 0N. The fertilizer N had no effect on total soil C or
chemically labile organic matter while the activity of hydrolase and oxidase enzymes in soil and
in both types of litter showed temporally variable response to N. The results of this study
indicate that N fertilization does not increase litter decomposition rates under no-till
management systems, had variable effects on soil enzymatic activity, and substantially reduced
soil CO2 flux in the lab.

ACKNOWLEDGEMENTS

I would like to acknowledge all my friends, colleagues and Professors whose help and
support made this research possible. My greatest thanks goes to my advisor, Dr. Stuart A.
Grandy, without whose guidance and encouragement my studies and research would have
been very challenging. I am also very thankful to members on my committee, Dr. Sieglinde
Snapp and Dr. David E. Rothstein for their helpful suggestions and comments that helped me in
refining my research work. Besides the committee members, I am also thankful to Kyle
Wickings for giving me valuable suggestions to steer through the research process.
I would also like to thank my colleagues and fellow graduate students who welcomed
me warmly and helped me in adjusting to the new environment. Being never abroad before, my
early days in the United States could have been very difficult without their joyful and loving
company. I am also grateful to the undergraduate technicians who assisted me in my research.
Finally and most importantly, I am grateful to my mother and my siblings for their love
and affection. I am also enormously indebted to my late father who gave top priority to the
education of his children. Though his absence is missed dearly, I am sure he would have been
happy to see his daughter graduating from a prestigious university.

iii

TABLE OF CONTENTS
LIST OF TABLES .................................................................................................................................... vi
LIST OF FIGURES ................................................................................................................................ viii

CHAPTER 1
REVIEW OF LITERATURE
INTRODUCTION ……….……………………………………………………………………………………………………………………….1
Soil Organic Matter .............................................................................................................................. 3
Mechanisms of Response .................................................................................................................... 6
Enzymes ...................................................................................................................................... 6
Hydrolytic Enzymes ......................................................................................................... 9
Oxidative Enzymes ........................................................................................................ 10
Litter Quality . ........................................................................................................................... 12
Initial Stage of Decomposition ...................................................................................... 12
Later Stage of Decomposition....................................................................................... 13
Microbial Community Structure ................................................................................................ 13
Microbial Respiration................................................................................................................. 15
Dissolved Organic Carbon .......................................................................................................... 16
Crop Residues in Agricultural System ................................................................................................ 17
CONCLUSION ..................................................................................................................................... 18

CHAPTER 2
NITROGEN FERTILIZATION EFFECTS ON LITTER DECOMPOSITION DYNAMICS AND
SOIL CARBON UNDER NO-TILL, CONTINUOUS CORN CROPPING SYSTEM.
INTRODUCTION ………….……………………………………………………………………………………………………..…………..20
MATERIAL AND METHODS ................................................................................................................. ..25
RESULTS…………………….. ........................................................................................................................ 32
DISCUSSION ...……………….…………………………………………………………………………..…………………………….…....35
Litter Dynamics ......................................................................................................................... 35
Soil Processes ............................................................................................................................ 39
iv

CONCLUSION ................................................................................................................................ ..43
LITERATURE CITED .................................................................................................................. …....61

v

LIST OF TABLES

TABLE 1:

List of microbial extracellular enzymes, their functions and classification.
(Adapted from ((A. S. Grandy, Neff, & Weintrau, 2007)). ......................................... 8

TABLE 2:

Soil and litter extracellular enzymes and their substrates ...................................... 28

TABLE 3:

Litter Chemistry: Relative abundance of chemical compounds in Corn and wheat
litters, measured in the beginning of the experiment (June, 2008) and at the end
(June, 2009). Where N = effect of Nitrogen, Ltr = effect of Litter and N*Ltr =
Nitrogen and Litter effect, na =the initial litter chemistry not subject to the three
(0,134,294 Kg/ha) N treatments. ............................................................................. 45

TABLE 4:

Light Fraction organic matter and C, N content per grams of soil and C:N ratios
measured in Jun and Aug 2008, where N = effect of Nitrogen, and T= effect of time
and N*T= effect of Nitrogen by Time. ..................................................................... 46

TABLE 5:

Inorganic NH4 and NO3+NO2 content of soil. ANOVA results consistent with
significant Nitrogen and Time interaction. .............................................................. 47

TABLE 6:

ANOVA of corn and wheat litter enzymes and Mass loss rates.Where CBH = β-Dcellobiohydrolase, BG = β-glucosidase, NAG = N-acetyl-β-D- glucosidase and
POX = Phenol Oxidase. AFDM= Ash free dry mass, N = effect of Nitrogen treatment
Ltr = effect due to litter type. .................................................................................. 48

TABLE 7:

ANOVA of soil variables with averages and standard errors in parentheses Where
CBH = β-D-cellobiohydrolase, BG = β-glucosidase, NAG = N-acetyl-β-D-glucosidase
and POX = Phenol Oxidase. CO2 =Cumulative CO2 flux from soil lab incubations for
125 days. N = significant effect of Nitrogen, T = significant effect of time, N*T =
interaction effect of Nitrogen and time, NS = Non significant ............................... 49

TABLE 8:

Correlations between soil and corn and wheat litter enzymes Correlation
coefficients in bold are significant (P<=0.05). Abbreviations: NAG (N-acetyl-β-Dglucosidase),CBH (β-D-cellobiohydrolase), BG (β-glucosidase),POX (Phenol
Oxidase).………………. ................................................................................................. 50

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TABLE 9:

Correlations between litter enzymes and the relative abundance of chemical
classes in litter Correlation coefficient in bold are significant (P = 0.05) Compound
abbreviations: Lip (Lipids), Poly(Polysaccharides), N-bearing (Nitrogen bearing
compounds)…….………………………………………………………………………………………………….51

vii

LIST OF FIGURES

FIGURE 1:

FIGURE 2:

A conceptual model showing direct and/or indirect effects of the inorganic
fertilizer- N and the subsequent effect on litter and soil C cycling
processes................................................................................................................. 36

Carbon mineralization monitored in a field study of corn nitrogen response at
the W.K. Kellogg Biological Station, Hickory corners, M Reported here as
cumulative soil CO2 emission from laboratory incubation of soil samples over
125 days. Samples were collected on June 17, July 09, August 05 and September
3rd of 2008. Analysis of variance (ANOVA) indicated a significant N rate effect
(P = 0.0001)............................................................................................................... 52

FIGURE 3:

Chemically labile organic matter (CLOM) monitored over the summer of (2008) in
a field study of nitrogen response at the W.K. Kellog Biological Station, Hickory
Corners, MI. Three levels of nitrogen were compared,
0,134,291Kg N/ha. ................................................................................................. 53

FIGURE 4:

Effect of 0, 134 and 291kgN/ha on decomposition rates of Wheat and Corn litter
at W.K.Kellog Biological Station,Hickory Corners,MI. ANOVA suggested
differences (P=<0.0001) between Litter types with higher mass remaining in
wheat than in Corn litter......................................................................................... 54

FIGURE 5:

Activity of N-acetyl-β-D-glucosidase (NAG) in soil, showing significant time
effect only under three levels (0, 134 and 291 KgN/ha) of N fertilizer treatment
measured from Jun’08 to Oct’08 at W.K. Kellogg Biological Station, Hickory
corners, MI ............................................................................................................. 55

FIGURE 6:

Activity of β-D-1,4-cellobiosidase (CBH) in soil under three levels
(0, 134 and 291KgN/ha) of N fertilizer rate measured from Jun’08 to Oct’08
at W.K. Kellogg Biological Station, Hickory corners, MI, with significant time effect
only.......................................................................................................................... 55

viii

FIGURE 7:

Activity of Phenol Oxidase (POX) in soil under three levels
(0, 134 and 291KgN/ha) of N fertilizer rate measured from Jun’08 to Oct’08 at
W.K. Kellogg Biological Station, Hickory corners, MI,with significant time effect
only. . ...................................................................................................................... 56

FIGURE 8:

Activity of β-1,4-glucosidase (BG) in soil under three levels
(0, 134 and 291KgN/ha) of N fertilizer rate measured from Jun’08 to Oct’08 at
W.K. Kellogg Biological Station, Hickory corners, MI with significant time effect
only.......................................................................................................................... 56

FIGURE 9:

Activity of β-1,4-glucosidase(BG) on wheat and Corn litters under three levels of
Inorganic Nitrogen Fertilizer (0, 134, 291Kg/ha), measured over a period of one
year from Jun’08 to Jun’09 W.K. Kellogg Biological Station, Hickory corners, MI.
ANOVA suggested a significant N by time interaction (P=0.05). ............................ 57

FIGURE 10:

Activity of β-D-1, 4-cellobiosidase(CBH) on wheat and Corn litters under three
levels of Inorganic Nitrogen Fertilizer (0, 134, 291Kg/ha), measured over a
period of one year from Jun,08 to Jun’09 at W.K. Kellogg Biological Station,
Hickory corners, MI. ................................................................................................ 58

FIGURE 11:

Activity of N-acetyl-β-D-glucosidase (NAG) on Wheat and Corn litters under the
effect of N fertilizer treatment (0, 134, 291Kg), measured over a period of one
year from Jun’08 to Jun’09 ..................................................................................... 59

FIGURE 12:

Activity of phenol oxidase on wheat and corn litters measured over a period of
one year from Jun’08 to Jun’09 under the influence of N fertilizer treatment
(0, 134, 291Kg N/ha) at W.K. Kellogg Biological Station, Hickory
Corners, MI.…………………………………………………………………………….. .......................... 60

ix

CHAPTER 1
REVIEW OF LITERATURE
INTRODUCTION
Increased N availability often increases plant biomass and litter inputs (Liu & Greaver,
2010). These above ground litter inputs represent the major contributions to the soil organic
matter pool (Sullivan et al., 2007) but below ground soil C may also increase (Alvarez, 2005),
decrease (Khan et al., 2007) or remain unchanged (Halvorson et al., 2002) in response to N
addition. This variation depends on the changes in the chemical composition of the litter and
/or the microbial activity in the soil. For example, Khan et al. (2007) reported that N fertilization
reduced soil C despite increased residue incorporation under continuous corn and reported an
even greater decline under corn-soybean and corn-oat rotation. Contrary to this finding,
Gregorich et al. (1996) reported higher C storage with increased fertilizer use and residue
inputs under continuous corn for 30 years. Similarly, a study conducted in temperate and
boreal forests in the Northern hemisphere showed an increase in C uptake by these forests
over a wide range of N deposition rates (Magnani et al., 2007). Due to the inconsistency of
these results, and the importance of soil organic matter dynamics in local, regional and global
processes, there is an urgent need to better understand the mechanisms associated with the
sequestration of soil organic carbon (SOC).
Agricultural soils in the US alone have lost nearly 30 to 50 Mg C/ha of SOC due to
cultivation (Lal, 2002). There is a growing concern about how high N availability in the soil
profile will affect C storage. Soil organic carbon (SOC) is the basis for most key soil functions,
plays a key role in the global C cycle, and is the foundation upon which sustainable agricultural
1

systems have historically been built. SOC influences soil quality by improving water holding
capacity of the soil and studies suggest that for every 1g increase in the SOM there is a 1 to 10g
increase in soil moisture (Emerson, 1995). SOC increases nutrient availability to plants by
increasing the cation exchange capacity (Johnston, 1986), and enhances soil structure and
aggregation (Feller & Beare, 1997). For all the aforementioned benefits of SOC, soils with high
SOC have the potential to give higher crop yields (Ganzhara, 1998; Zhukov et al., 1993). Further,
C sequestration has been suggested by many researchers as a means to restore degraded soils
and increase their productivity (Lal, 2006). Thus not only is SOC important for improving soil
quality and productivity but its storage in soil can help offset atmospheric increases in CO2
(Pretty & Ball, 2001).
SOC sequestration depends on the additions and losses of carbon in soils (Christopher
& Lal, 2007). The balance between additions in the form of net primary production (NPP) of
crops or other organic inputs such as manure and the losses by decomposition determines the
quantity of SOC storage (Russell et al., 2009).
ΔSOC = additions – losses
However, these gains and losses in SOC are influenced by many factors including moisture,
temperature, soil type and land management factors such as tillage and fertilization (Russell et
al., 2009).

2

Nutrient inputs in the form of fertilizer can have a profound impact on soil carbon through:
I.

increasing net primary production

II.

influencing the decomposition rate of SOC (increase or decrease) and

III.

changing the chemistry of plant tissues, which can influence their decomposition rate.
Historically, it was widely thought that SOC would increase – at least in agricultural

systems – with N enrichment because of the increased productivity and residue inputs.
However, highly variable results across a number of studies suggests that there is an
uncertainty regarding the response of soil carbon to N enrichment due to N deposition from
fossil fuel combustion and the intensive use of N fertilizer in the agricultural systems. If N
enrichment influences the rate of decomposition by changing microbial activity or the microbial
community composition and the chemistry of the litter, soils could either lose or gain soil C and
its associated functions
Soil Organic Matter: Soil organic matter (SOM) formation is a complex process that includes the
processing of leaf litter, plant residues, soil organisms and manure. The ‘living matter’ of the
organic matter includes the plants, animals and microbes and it becomes a part of the ‘nonLiving matter’ when it goes through the decay process after death. Cellulose and hemicellulose
are the most abundant polysaccharides in plant tissues. Although these compounds are not as
recalcitrant as lignin, they are often protected from microbial decomposition by aromatic
compounds, (Carreiro et al., 2000). The different plant constituents are degraded by different

3

classes of enzymes produced by microbes in the following order, starting from least to most
recalcitrant compounds:
Amino acids > Hemicellulose > Cellulose > Lignin
Reflecting the variation in plant tissue and microbial residue chemistry, organic matter is
extremely heterogeneous and consists of an incredible diversity of compounds that range in
their chemical structure, turnover time (Walcott, Bruce, & Sims, 2009), origin, and behavior in
soil (Grandy et al., 2009). Soil scientists are always looking for ways to better understand SOM,
its composition and behavior.

Thus, a number of fractionation procedures have been

developed that separate SOM into different fractions with discrete behavior.

In a recent

paper, Walcott et al. (2009) partitioned SOM into the following categories:
Dissolved organic matter: an energy source for microbial metabolism. It is a small fraction of
the total soil carbon and its composition ranges from simple amino acids to complex high
molecular weight molecules and comprises a small proportion of SOC at any one time (Neff &
Asner, 2001).
Particulate Organic matter: is the partially decayed plant and animal tissue that is in a
recognizable form it includes the organic matter at soil surface, the organic matter > 0.053mm
in diameter and the light fraction that floats when the soil is wetted.
Humus: comprises about 50-60% of the total soil organic matter, is produced by the
decomposition of plant and animal matter and is not in a recognizable shape and is dark
colored.

4

Inert organic matter: also called the recalcitrant material that comes from burning and includes
charcoal or charred material.
Furthermore SOM can be divided into light fraction (LF) and heavy fraction (HF) pools
based on their chemical composition and their association with the different soil classes.

The

‘light fraction’ SOM, which is associated with coarse soil fraction is generally identifiable,
unprotected young plant material with high C concentration, most of which is lost during initial
degradation process (Ellert & Gregorich, 1996; Gleixner, Poirier, Bol, & Balesdent, 2002).

The

‘heavy fraction’ is stable and has lower C concentrations (Golchin et al.,1995; Golchin et al.,
1995).

It contains mostly the microbially-derived N compounds and stabilized aromatic

compounds (Guggenberger et al., 1994) that are ‘physically protected’ against microbial
decomposition by association with clay surfaces and through encapsulation inside an aggregate.
Therefore, well aggregated fine textured soils can typically accumulate more C than sandy soils.
Hence based on the above discussion, the decomposability of LF and HF of SOM decreases in
the soil classes in the following order:
sand > silt > clay
Increased soil N availability might influence the decomposition of SOM pools in different ways:
I.

higher microbial activity in LF organic matter could lead to C losses, especially in coarse
soils that provide little physical protection (Grandy & Neff, 2008);

II.

accumulation of HF due to selective suppression of the microbial enzymes required to
decompose complex molecules (e.g. lignin).

5

III.

changes in the chemistry of the litter or the crop residue due to differential
decomposition of polysaccharides and polyphenols in the LF and the HF pools; and

IV.

N is known to bind with carbohydrates in soils and make ‘melanoidins’ (Fog, 1988;
Soderstrom, Baath, & Lundgren, 1983) which can increase the polymerization of
polyphenols into ‘brown’ compounds (Haider & Martin, 1967), both of which are
resistant to microbial degradation, thus providing ‘biochemical protection’ to SOC
(Kogel-Knabner, 2002).
It is important to understand how the availability of inorganic N can change the

dynamics of the decomposers and their activity in different SOM pools as the amount of C
accumulated in one pool can be offset by the accelerated microbial degradation in another
pool. Following is a discussion about how inorganic N might influence microbial activity and
other associated mechanisms regarding SOC sequestration.
Mechanisms of Response:
Enzymes: Because of the complexity of SOC dynamics, in particular the interactions between
soil communities, their enzyme systems, and different C compounds, the effect of N addition on
decomposition remains uncertain. Microbial enzyme responses to N addition have been
studied by many researchers to understand whether enzymes may help explain the variation in
soil C responses to N. The long term addition of N can have neutral, positive or negative effects
on decomposition rates, and the variability in enzyme responses to N may be one explanation
for this variability as not all types of enzymes respond in similar way to the availability of N
(Fog, 1988).
6

Enzymes are N-rich compounds and their production is regulated by the availability of
inorganic N. Thus the variation in their response to N addition can be considered a good
predictor of N effect. There are two classes of microbial enzymes, hydrolytic and oxidative
enzymes, which degrade cellulosic and lignified compounds respectively. The hydrolytic
enzymes include endoglucanases, exoglucanases and β-glucosidases (Table:1). These are
produced by a large group of bacteria and certain fungal species and are associated with the
decomposition of cellulose, chitin, and storage carbohydrates, whereas phenol oxidase and
peroxidase are the oxidative enzymes responsible for the degradation of aromatic secondary
phenolic compounds including lignin (Gallo et al., 2004). Oxidases are produced by fungi
(Table:1).

Phenol oxidase uses oxygen to degrade phenolics whereas peroxidase uses H 2O2 as an
electron acceptor. Phenol oxidase is the only lignolytic enzyme produced by the white rot fungi
in the basdiomycota and xylariaccous Ascomycota (Dix & Webster, 1995) (Table:1). Microbial
lignin degradation results in the production of polyphenols. These are central reactive
molecules in the formation of organic matter and can also be formed through microbial
synthesis from a non-lignin carbon source such as cellulose.

7

Enzyme

Enzyme Function

β-1,4-glucosidase

Catalyzes the hydrolysis of terminal 1,4 linked β-D- 4-MUB-β-Dglucose residues from β-D-glucosides, including short glucoside
chain cellulose oligomers.

α-1,4-glucosidase

Principally a starch degrading enzyme that catalyzes 4-MUB-α-Dthe hydrolysis of terminal, non-reducing 1,4-linked α glucoside
-D-glucose residues, releasing α-D-glucose

β-D-1,4cellobiosidase

Catalyzes the hydrolysis of 1,4-β-D-glucosidic linkages 4-MUB-β-Din cellulose and cellotetraose, releasing cellobiose.
cellobioside

β-1,4-N-acetylglucosaminidase

Catalyzes the hydrolysis of terminal 1,4 linked N- 4-MUB-N-acetyl-βacetyl-beta-D-glucosaminide
residues
in D-glucosaminide
chitooligosaccharides (chitin derived oligomers).

Leucine
peptidase

Substrate

amino Catalyzes the hydrolysis of leucine and other amino L-Leucine-7-aminoacid residues from the N-terminus of peptides. 4-methylcoumarin
Amino acid amides and methyl esters are also readily
hydrolyzed by this enzyme.

Phenol oxidase

Also known as polyphenol oxidase or laccase. Oxidizes L-DOPA
benzenediols to semiquinones with O2.

Peroxidase

Catalyzes oxidation reactions via the reduction of L-DOPA
H2O2.
It is considered to be used by soil
microorganisms as a lignolytic enzyme because it can
degrade molecules without a precisely repeated
structure

Table 1: List of microbial extracellular enzymes, their functions and classification.(Adapted from
((A. S. Grandy, Neff, & Weintrau, 2007)).

The extracellular enzyme activity for the degradation of lignin and cellulose has been
correlated with rates of litter and organic matter decomposition. Given the close association
between microbial enzyme activity and SOC dynamics, enzymes can provide us with insight into
the functional response of the microbial community to anthropogenic N addition. There are
8

many hypotheses regarding the specific effects of N addition on enzyme activity and
decomposition rate. These hypotheses are not mutually exclusive and in any given system
there may be several in play at the same time, which could help explain the complex responses
of SOC to N:
I.

N increases the randomization of the chemical bond structure of organic material,
thereby reducing decomposition rates and stabilizing soil C (Fog, 1988).

II.

Hhigh N stimulates the activity of hydrolytic enzymes which are responsible for the
degradation of more labile C (Carreiro et al., 2000; Sinsabaugh et al ., 2002)

III.

Suppression of the microbial oxidase enzymes due to increased availability of the
inorganic N may result in reduced lignin decomposition (Fog, 1988);

IV.

N addition alters the composition of the decomposer community in a way that slows
down its overall degradation ability (Bardgett et al., 1999; Frey et al., 2004) and

V.

N addition changes the chemical composition of litter and organic matter over time.
Following is a discussion that encompasses these hypotheses:

Hydrolytic Enzymes: Cellulose is a major component of plant material and its degradation is
mediated by a group of functionally similar hydrolytic enzymes collectively called ‘cellulase’.
The activity of this enzyme system is known to be limited by the availability of N in nature.
Therefore N is a critical element and its higher concentrations, either in litter or in the soil
solution may accelerate the decay process in the early stages, when the litter has higher
cellulose content (Mellilo et al., 1982; (Fog, 1988). This hypothesis has been well studied in non9

agricultural systems (Carreiro et al., 2000; Geisseler & Horwath, 2009; R. L. Sinsabaugh et al.,
2002). Carreiro et al., (2000) reported an increase in the hydrolytic enzyme activity in the more
labile cellulosic litter such as, flowering dogwood, red maple and red oak. Interestingly, the
positive response of this enzyme often shown in response to N may decline during the course
of decomposition. Although the specific mechanisms are not well known, possible explanations
include:
I.

High N suppresses lignin degradation which results in the accumulation of phenolics,
which have an inhibitory effect on hydrolase enzymes (DeForest et al., 2004; DeForest
et al., 2005; Dijkstra et al., 2004; Fog, 1988; Freeman et al., 2001)

II.

Since much cellulose is bound in lingo-cellulose complexes, and the degradation of
lignin is inhibited by the presence of N, carbohydrates may be protected from microbial
decay (DeForest et al., 2004).
Oxidative Enzymes: The effects of N on the activity of lignin degrading enzymes have been

examined primarily in forest ecosystems. Both phenol oxidase and peroxidase have been found
to exhibit a reduced activity under high N availability, and phenox is shown to respond more
strongly to N addition in comparison to peroxidase (DeForest et al., 2004; Gallo et al., 2004). For
example, Carreiro et al. (2000) found reduced activity of phenol oxidase in litter with a high
lignin content (oak leaves) and argued that although lignin degrading enzymes are produced by
some bacteria, the ‘white rot fungi’ from the Basidiomycota and xylariaccous Ascomycota (Dix
& Webster, 1995) are the only fungi known to produce phenol oxidase. Therefore, fungi are
considered the principal degrader of lignin. Hammel (1997) suggested that the decreased
10

activity of phenox oxidase in lignified oak litter in their study could be due to either suppression
of the synthesis of the enzyme by white rot fungi or to reduction in their overall abundance.
This assumption regarding the abundance of the lignin degrading fungi has been well explored
and many studies have reported that the reduced lignase activity was not correlated to
reduction in the abundance of this fungi in response to N (DeForest et al., 2004; Galloway &
Cowling, 2002).
Waldrop et al (2004) correlated phenol oxidase activity with decomposition rate and
observed a high decomposition rate at sites where there was high phenol oxidase activity and
low decomposition rates at sites with low phenol oxidase activity, suggesting that the response
of this enzyme is crucial in determining soil C dynamics. Similarly, Carreiro et al (2000) also
supports this finding and suggests that the response of this enzyme is a good indicator of
changes in decomposition rates due to N addition. In contrast to the above explanation of
reduced decomposition rate, another view is that microbes synthesize phenolic compounds
during degradation that react with inorganic N and form ‘browning precursors’ that are toxic
and/or inhibitory to microbes and suppresses their activity (Couteaux et al., 1995). Regardless
of what the mechanism of reduction in the oxidase enzyme activity might be, the suppressed
activity of this enzyme can help accrue SOC in the long run. In relation to N effect on
mechanisms, the more convincing evidence of N addition effect comes from the studies on the
decomposition rates of litter and the related changes in its chemistry, partly due to differential
activity of the hydrolytic and oxidative enzymes:

11

Litter Quality: Litter decomposition involves the mineralization and humification of plant
material (hemicelluloses, cellulose, lignin) by microbes (Couteaux et al., 1995). The quality of
litter, availability of nutrients and structure of the decomposer community are primary controls
on litter decomposition (Berg & Matzner, 1997; Couteaux et al., 1995; Knorr et al., 2005). For
example, Neely et al. (1991) measured decomposition in agricultural systems using a litter bag
experiment. A wide range of litter types were used including crimson clover, hairy vetch,
crabgrass, grain sorghum and wheat.

They reported significant differences in the

decomposition rates between the species and observed that the initial N concentration of the
litter was the best predictor of decomposition rate and found a linear relation of initial N and
decay rates for all the species. These results suggest that N is an extremely important driver of
the differences in decomposition rates between species, and also suggest that the application
of external N may be a key driver of decomposition.
However, there is considerable evidence that the quality of litter strongly influences its
response to N enrichment. This is reflected in two phenomena that have frequently been
reported. First, the chemistry of litter, in particular its lignin and polysaccharide contents, is
often correlated with N response. Second, several studies suggest that N addition can have
different effects on litter decomposition rate in its early and later stages, which is likely due in
part to changes in chemistry during decomposition.
Initial stage of Decomposition: Fresh litter often contains insufficient nutrients to meet
microbial needs (Aber et al., 1991), which has been shown by immobilization of N in the initial
stages of litter decomposition (Berg & Matzner, 1997; Hobbie, 2000). Nutrient limitation in the

12

early stages of decomposition can be overcome by the addition of N. Therefore, decomposition
rates often increase with the application of nutrients (Hobbie & Vitousek, 2000). In particular,
studies often report a rapid disappearance of cellulose due to N applications increasing
cellulose degrading enzyme activity in the initial stages of decomposition (Berg, 2000; Hobbie &
Vitousek, 2000; McClaugherty et al., 1985). Similarly, Berg and Ekbohm (1991) reported that the
most nutrient rich litter types exhibited rapid decomposition in the beginning of
decomposition. They also observed that the initial lignin content in the litter had a negative
relation with mass loss. We find similar results in other studies as well (Berg, 2000; Berg &
Meentemeyer, 2002; Neely et al., 1991), indicating that the addition of N to litter with high
cellulose and relatively low lignin contents can increase decomposition rates, particularly in the
early stages of decomposition.
Later stage of Decomposition: A negative effect of N availability on mass loss in litter
with high lignin concentration has been frequently reported. The suggested rationale behind
the rate decline is that low weight molecular N compounds repress the production of lignolytic
enzymes in certain fungal species (Berg & Meentemeyer, 2002). Another suggested mechanism
is that as decomposition proceeds and the products of lignin degradation accumulate, they
react with the available N to form compounds which are resistant to further degradation (Fog,
1988). Thus, it is expected that the suppressive effects of N will be strongest in the later stages
of decomposition when lignin concentrations in litter are at their highest.
Microbial Community Structure: With the introduction of molecular based techniques in
assessing microbial functional and taxonomic diversity in recent years, we have a better

13

understanding of the response of the microbial community to N enrichment. Many studies have
reported changes in the function of the microbial community based on the changes in enzyme
activity and respiration rates in response to N addition. Therefore, one might also expect a
change in the microbial community structure as well, resulting from either a direct or indirect
effect of N on microbial communities. A decrease and/or inhibition of enzymes, for example,
can hamper a community’s ability to derive energy and could change the patterns of microbial
community substrate use and ultimately microbial biomass, fungal:bacterial ratio or the relative
abundance of specific decomposers. Other indirect effects on communities may be mediated
by changes in litter inputs or microbial biomass.
Studies suggest that N increases above ground plant biomass and litter inputs into the
soil (Liu & Greaver, 2010; Sylvia, Fuhrmann, & Hartel, 1999). Based on this, we can hypothesize
that with high aboveground inputs there would be high nutrient availability which in turn will
affect the belowground microbial population, but this may not necessarily be true for the MBC.
For example, Deforest et al. (2004) conducted a study in Northern Hardwood stands in
Michigan and reported a significant decline in overall microbial biomass carbon (MBC) with no
effect on fungal: bacterial ratio. Similarly, Treseder (2008) conducted a meta analysis including
82 field studies and reported a 15% decline in the overall MBC in response to added N. These
results have been supported by other studies as well (Compton, Watrud, Porteous, & DeGrood,
2004; Frey et al., 2004; Liu & Greaver, 2010). For example, Kaur et al., (2008) reported a
significant decline in MBC with N application under wheat-corn rotation and argued that this
negative effect might be due to the effect of N on soil pH. Henriksen and Breland (1999) also
observed a decline in fungal biomass with no effect on bacterial biomass in a wheat straw
14

decomposition experiment under increased availability of N. Frey et al., (2004) also reported a
significant decline in fungal biomass after N addition and observed a significant decrease in
phenol oxidase activity. Similar results have been reported by other studies as well (Allison et
al., 2007; Frey et al., 2004; Nemergut et al., 2008; Treseder, 2008) .
Microbial Respiration:

Bowden et al., (2004) conducted a study in red pine and mixed

deciduous stands and observed increased soil respiration with N addition in the first year but
reductions in respiration in subsequent years. They obtained similar results in lab incubations
of root-free soil as well. They attributed the increase in CO2 flux in the first year to the
increased aboveground biomass in the form of litter fall, and suggested that a decrease in
respiration in the later years could be due to reduction in decomposer efficiency due to either
inhibition of enzyme production or reduction in the MBC. It is possible that in the field N
addition initially accelerates decomposition of fresh litter due to increased enzyme activity.
This, plus any initial increases in litter inputs could increase respiration rates in the short term.
Although there may be short-term increases in soil respiration, most studies show long-term
decreases in respiration. These declines may be due to declines in fungal abundance and
biomass and the inhibition of lignin-degrading enzymes. This has been supported by Frey et al
(2004), who found N reduced fungal biomass and phenol oxidase activity. In addition Al-Kaisi et
al., (2008) observed inconsistent respiration rates under corn-soybean rotation and attributed
it to changes in moisture and temperature, but they found a significant decrease in the lab
incubations of the soil under high N. Kowalenko et al., (1978) also observed reduced CO2 in field
measurements and lab incubated soils. The decrease in soil respiration has been reported in

15

several other studies (Foereid et al., 2004; Wilson & Al-Kaisi, 2008) but the mechanism for the
decrease in the CO2 emissions under high N are not clear but have been correlated to
reductions in MBC and enzyme activity. Soil pH has also been suggested for a decrease in MBC
and CO2 emissions (Aerts & de Caluwe, 1999; Bowden et al., 2004). Increased nitrification of
ammonium in soil results in acidification, thus reducing MBC and CO2 emissions.

Dissolved Organic Carbon:

Another way that N enrichment influences SOC dynamics is

through changes in dissolved organic carbon (DOC). It is a small fraction of the total soil carbon
and its composition ranges from simple amino acids to complex high molecular weight
molecules (Neff & Asner, 2001) containing readily available C sources for microorganisms
(Sylvia et al., 1999). Studies have shown an increase in DOC with N enrichment (DeForest et al.,
2004; Liu & Greaver, 2010; Pregitzer et al., 2004; Sinsabaugh et al., 2004)
It is important to understand the mechanisms for the increase in DOC because it might
result in the loss of SOC through leaching from the soil profile. The increase in DOC can be
explained by increases in plant biomass inputs to soil. Lebauer and Treseder (2008) found that
N additions increased aboveground litter production, which increased soil C availability and
resulted in higher C losses by leaching. Similarly the negative effect of N addition on lignase
enzyme activity, fungal biomass and MBC has been well established and that might have a
direct effect on DOC consumption and availability. Sinsabaugh et al. (2004) observed in their
study that increases in DOC were parallel to the decrease in oxidase enzyme activity suggesting
that there is a lower consumption of DOC due to lower microbial activity in response to high N.

16

In addition Pregitzer et al., (2004) also observed increases in DOC leaching from N amended
plots with a simultaneous decline in respiration.
Crop Residues in Agricultural System: Along with the quantity, the quality of the crop residue is
also crucial in C sequestration. Although all plants contain similar classes of compounds they
differ in their proportions and thus decomposability varies with different species (Hadas,
Kautsky, Goek, & Kara, 2004). The C and Nitrogen concentrations are considered important
indicators of crop residue quality (Kononova, 1961) as these give us insight into the rate and
extent of decomposition by microbes and hence the potential to sequester C. C/N ratios of the
crop residues depend on the crop species. For example corn and wheat residues have high
phenols and C/N ratios, which will result in low decomposition rate and increased SOC (Russell,
Laird, Parkin, & Mallarino, 2005) in comparison to soybean (Glycine max L.) which has lower
phenols and C/N ratio and decompose readily and hence contribute less to the SOC content. In
a meta-analysis Knorr et al., (2005) conclude that low quality litter with high lignin content
decomposed faster than the high quality litter with increased availability on N. However C/N
ratio of the crop residue is not the only factor regarding the quality of the residue that controls
decomposition rate as some researchers have reported that high concentrations of N in the
SOM were not responsible for the decomposition rate (Hobbie & Vitousek, 2000).

17

Conclusion
Due to inconsistency in the results in the response of microbes and the associated
mechanisms to N addition, it is hard to draw a general conclusion, but the above discussion
can be summarized as follows:
I.

Increased availability of inorganic N due to N deposition or agricultural management
practices in soils may accelerate SOC losses and diminish soil quality.

II.

N addition accelerates the decomposition of labile litter but it can slow the
decomposition of more recalcitrant litter. Therefore, N addition in the long run might
result in the accumulation of SOC in ecosystems characterized by high-lignin litter.

III.

The role of lignin degrading enzymes can be critical due to their strong response to N
addition. The C quality and the N content in the substrate (litter or crop residue)
degraded by microbes plays primary controls over decomposition rate. If lignin content
is high, we can expect an increase in SOC.

IV.

The inhibition of microbial enzymes and reduction in MBC and soil respiration could
result in SOC loss in the form of increased DOC leaching.

V.

Land use for agricultural purposes has substantially reduced topsoil C. The SOC
sequestration in agricultural systems can improve by proper N fertilization and crop

18

residue management in combination with reduced tillage and improved cropping
system management.

19

CHAPTER 2
NITROGEN FERTILIZATION EFFECTS ON LITTER DECOMPOSITION DYNAMICS AND
SOIL CARBON UNDER NO-TILL, CONTINUOUS CORN CROPPING SYSTEM.

INTRODUCTION
Human activities, including N fertilization, the cultivation of N fixing crops, and fossil
fuel combustion, have more than doubled the global flux of biologically reactive N (Vitousek et
al.,1997; Galloway et al., 2004). This increase in available N is linked to accelerated nitrous
oxide flux (Bouwman et al., 2002a, 2002b; Mosier et al., 1998), ecosystem acidification (Bolan,
Hedley, & White, 1991), reduced water quality (Hallberg, 1987), and changes in plant species
distribution and abundance (Chung et al., 2007; Dybzinski et al., 2008; Vitousek et al., 1997).
However, the effects of reactive N on decomposition dynamics have proven variable and
remain difficult to predict, owing in large part to uncertainties about how soil biological
communities respond to inorganic N. Our knowledge of the relationships between inorganic N,
soil communities, and decomposition dynamics is particularly limited in agricultural systems.
Although the majority of recent efforts to understand N effects on decomposition processes
have been carried out in non-agricultural soils, N inputs to agricultural soils increased from 12
to 104 Tg/yr (FAO, 2009) globally over the last 40 years, and will continue increasing in the
decades ahead as the global population approaches 10 billion people. Further, the rate of N
application to most high-yielding, intensively managed cropping systems is high. In the U.S.
Corn Belt, for example, the average rate of N application to corn is ~135 kg N/ha ,or more than

20

an order of magnitude greater than the rates of atmospheric N enrichment in most U.S.
ecosystems (Russell, Cambardella, Laird, Jaynes, & Meek, 2009)
Soils contain approximately 1580 PG of C in the form of organic matter and surface
litter (Schlesinger, 1997), which is more than the combined amount in vegetation and in the
atmosphere. Agricultural land use, however, has reduced top soil C by ~35-55% and the
restoration of this lost C is one of only a few short term, high impact options proposed to
stabilize atmospheric CO2 concentrations. (Christopher & Lal, 2007) Soil C sequestration is also
attractive to many land managers and policy makers because of its positive effects on soil
fertility, water dynamics, and erosion control (Smith ,2004; Bell et al., 2009), and is thus
considered a ‘win-win’ scenario with benefits to producers and society at large. While the best
methods to sequester soil C are still being established, SOM concentrations are in part a
function of soil C inputs. Given the relationship between soil C inputs and SOM concentrations
(Campbell et al., 1991), agronomists often attempt to increase plant productivity through
expanded fertilizer use, the development of high yielding varieties and other practices such as
reduced or no-tillage (VandenBygaart et al., 2003) and crop rotation (Wilson & Al-Kaisi, 2008).
However, recent long-term field experiments and new insights into the priming effect call into
question the links between fertilizer use, crop yields and SOM concentrations. Is it possible
that N use in agricultural systems is increasing C inputs but decreasing soil organic matter
decomposition via accelerated decomposition rates?
Recent work by Khan et al., (2007) suggested just this dynamic has been at play in the
Morrow plots in Illinois. They examined long-term soil C data and found that the initiation of

21

inorganic N fertilizer use corresponded with a long-term decline in SOM concentrations, despite
increases in plant productivity. However, these observed changes may have also been due to
changes in climate and/or the diversity of residue inputs that coincided with the onset of
inorganic N fertilizer applications. Russell et al., (2009) found that under four levels of N
fertilization 0,90, 180, 270Kg/ha there was a significant increase in aboveground net primary
production and thus total organic C inputs with N addition but they also observed higher
decomposition rate with high N such that the high decay rates offset higher inputs and net C
sequestration was nil. Other studies have shown that synthetic N application in agricultural
systems can increase soil CO2 emissions and soil C loss (Al-Kaisi et al., 2008), but results are
mixed and reports show accumulation (Reay et al., 2008; Al-Kaisi et al., 2008; Poirier et al.,
2009), loss (Hofmann et al., 2009; Khan et al., 2007; Mulvaney et al., 2009) or no change in soil
C (Halvorson et al., 2002). Further, disentangling the effects of N fertilizer from other forms of
agricultural disturbance that influence biogeochemical processes, including tillage and reduced
plant community diversity, can be difficult under most experimental designs.
Our understanding is also limited by the scant number of studies in agricultural
systems that have focused on how soil biological processes that control decomposition
dynamics and soil C – rather than soil C, per se - respond to N. Measuring changes in soil C
stocks is notoriously difficult because soil C concentrations are high and spatially variable
(Conant et al., 2003; Robertson et al., 1997). Because of this, a decade or more may be needed
to detect significant changes in SOM pools. Further, some long-term experiments investigating
soil C responses to inorganic N are not replicated, or changes in N fertilizer use may be
confounded by other changes in management. An alternative, complimentary approach is to
22

focus on the short term biological processes that control decomposition and their responses to
N. Such an approach avoids the need to detect changes in total soil C stocks while providing
fundamental insights into the processes controlling C cycling.
In forest and grassland ecosystems, studies have shown changes in soil communities,
enzymatic activities, and decomposition rates following simulated N enrichment. For example,
many studies have shown that N inhibits oxidase enzymes as well as the decomposition of
lignin, while accelerating the activity of hydorlases and the degradation of labile C pools
changing microbial communities (Carreiro et al., 2000; Sinsabaugh et al., 2002; Frey et al., 2004;
Hofmann et al., 2009). Recent studies indicate that these changes in biological processes may
be accompanied by shifts in the chemistry of soil organic matter (Neff et al., 2003; Gallo et al.,
2005). For example, Grandy et al. (2008) found that N additions to forest ecosystems increased
the ratio of lignin:nitrogen in coarse soil fractions >63 µm, and also increased the ratio of
lignin:polysaccharides in soil fractions

>250 µm.

They also found that N increased the

abundance of specific polysaccharides, but all of these effects depended on ecosystem type.
The mechanisms underlying changes in litter chemistry following N fertilization are not well
known, but these changes in chemistry appear to correspond with shifts in soil enzyme activity.
Other studies have also demonstrated strong relationships between changes in soil
communities, enzyme activities, and the chemistry of litter after decomposition (Grandy et al.,
2009; Wickings et al., 2010), but none of these studies have explored such relationships in
agricultural systems. Together, these studies suggest that N-induced changes in decomposer
communities may influence organic matter chemistry via changes in soil decomposer
communities.
23

In recent years, major advances have been made in understanding the environmental
consequences of intensive N fertilizer use in agricultural systems, mainly N leaching and
denitrification (Aber et al., 1998) but few studies have used high-resolution biological and
biochemical methods to resolve decomposition responses to N in agricultural systems. While it
is well established that agricultural conversion accelerates soil C cycling, (Lal, 2002) few studies
have decoupled the direct effects of N fertilization from associated changes in plant chemical
composition and community diversity, tillage intensity, and edaphic soil properties (e.g. pH).
To better understand how inorganic N fertilizer influences decomposition in agricultural
systems, I examined litter decomposition rates, decomposer communities and processes (soil
enzymes, and microbial communities), and soil C pools, enzyme activities and chemistry along
an agricultural N fertilizer gradient. The objective of this study is to investigate the effects of N
fertilizer application on microbial activity, decomposition dynamics, and soil C storage. Given
previous studies suggesting that decomposition responses to N are regulated by litter quality, I
hypothesized that N fertilizer would accelerate biological processes and decomposition rates in
corn litter but suppress decomposition rates in wheat litter, which has higher lignin
concentrations and lower polysaccharide concentrations (Ghidey & Alberts, 1993). These
differences in litter decomposition rates will be associated with changes in litter enzyme
activities. I also anticipated changes in soil enzyme activities and labile, readily degradable SOM
pools hence effecting soil C pools.

24

MATERIAL AND METHODS
Site Description: This study was carried out at the N Fertility Gradient Study at the W.K. Kellogg
Biological Station Long-Term Ecological Research (LTER) site. This site was established in the
year 2005. This site has been under corn-soybean-wheat rotation and prior to its establishment
these plots were under alfalfa. The mean annual precipitation at the KBS LTER site is ~ 890
mm/yr and soils are classified as Kalamazoo (fine-loamy) and Oshtemo (coarse-loamy) mixed,
mesic, Typic Hapludalfs (Alfisols) developed on glacial outwash (Crum and Collins 1995).
Experimental design: This study consists of a continuous corn, no-till cropping system fertilized
at 9 different N levels ranging from 0 to 291 kg N/ ha. Experimental plots are 5 x 30 m,
replicated four times, and arranged in a randomized complete block design. Along the N
fertility gradient, we examined three treatments, 0, 134, and 291 kg N/ha, representing zero,
optimum, and very high N, respectively. Nitrogen was applied during May and June of 2008.
May fertilizer N was applied at 34 kg N/ha as a starter fertilizer to all plots except for control
and the June fertilizer was applied at zero, 100 and 257 kg N/ha as 28 % urea-ammonium-N
using subsurface, side-dress injection when corn was at a height of 10-25 cm. Our rationale for
using these rates of N fertilizer was to have experimental treatments with very different levels
of soil N availability, representing: 1) N limitation, in which crop N demand would exceed soil N
availability; 2) relative synchrony between total crop N demand and N availability; and 3) N
saturation, in which N availability exceeds crop demand through the season.

25

Litterbags and soil sampling: Standing dead corn plants and wheat straw were collected in fall
2007 from sites managed according to MSU best management practices. These plants were
selected because they represent litter types with different initial chemistries, but also because
they represent the majority of C entering field cropping systems in the upper Midwest. Studies
have shown that compared to corn and wheat very little aboveground residue from soybean is
incorporated into stable soil C pools. Indeed, the vast majority of aboveground soybean
residue is decomposed within months (Wickings et al. 2010) at KBS. Air dried corn or wheat
litter was cut into 2-4 cm pieces, homogenized, and placed into 7 x 7 cm nylon mesh litter bags.
Litterbags, measuring 18 x 18 cm and with a mesh size of 1.4 mm were filled with 7 g of either
corn leaves and stems or wheat straw and secured to the soil surface in June 17, 2008. Each
plot received six litter bags for each type of litter, representing the six time steps.
The placement of the litterbags on the soil surface mimics the deposition of
aboveground residues in no-till systems, which typically accumulate surface litter. Therefore,
this litter does not receive a direct fertilizer application because the fertilizer is injected into the
soil, which is also typical in no-till systems. Although our design may not maximize the
potential to see a N fertilizer effect on litter decomposition dynamics, there have been many
studies designed to broadly test the potential for N to influence decomposition dynamics, often
under unrealistic scenarios. In our case, even the highest rate of N fertilization was carried out
under otherwise realistic no-till management conditions. Given the possibility that soil-injected
N may not influence aboveground litter decomposition, we also made intensive measurements
of soil responses to different fertilizer rates.

26

At sampling, 10 soil cores were taken randomly per plot to a depth of 10 cm from all the
12 plots along with 24 litter bags (12 bags for both types of litter). Soil and litter bags were
collected at approximately monthly intervals (July 08, Aug 08, Sept 08, May 09, June 09) and
transported to the lab on ice where they were sub-sampled for the physical and biological
analyses.
Extracellular Enzyme Activity: Subsamples of 0.5 g litter and 1 g soil were homogenized with 40
ml of 50 mM sodium acetate buffer at a pH of 6.5 and 6.0. The slurries were then used to assess
the activity of five extracellular enzymes involved in carbon and nutrient cycling following the
methods reported in Saiya-Cork et al. (2002) and Grandy et al. (2007). The activity of three
hydrolase

enzymes,

β-glucosidase(BG),

N-acetyl-β-D-glucosidase(NAG),and

β-D-

cellobiohydrolase(CBH),were assessed using black, 96-well microplates and compound-specific
substrates containing the synthetic fluorescing molecule methylumbelliferone. The substrates
for these enzymes were 4-MUB-β-D-glucoside for BG, 4-MUB-Nacetyl-β-D-glucosaminide for
NAG, and 4-MUB-B-D-cellobiosidase for CBH. The activity of one oxidative enzyme (phenol
oxidase) was also measured using clear 96-well microplates and the substrate, L-dihydroxyphenylalanine (L-DOPA) to assess the breakdown of lignin. All plates were incubated for a time
period approximate for each enzyme (Table.2). The hydrolase enzyme activity was determined
using a flourometer (355 μm excitation and 460 μm filter range) and phenol oxidase activity
was measured using a spectrophotometer with a 450 μm filter (Thermo Fisher Flouroskan and
Multiskan).

27

Enzyme
Type
Substrate
β-glucosidase
Hydrolase 4-MUB-β-D-glucoside
N-acetyl-β-D-glucosidase
Hydrolase 4-MUB-Nacetyl-β-D-glucosaminide
β-D-cellobiohydrolase
Hydrolase 4-MUB-B-D-cellobiosidase
Phenol oxidase
Oxidase
L-dihydroxy-phenylalanine
TABLE.2: Soil and litter extracellular enzymes and their substrates

Mass Loss: The decomposition rate of the litter was determined by the method as described in
Robertson et al. (1999). Any roots attached to the litter bags were carefully removed and air
dried. The mass of the air dried litter was recorded and a 0.5 g sub-sample of the ground litter
was ashed at 450 °C for 4 hrs in a muffle furnace to determine the ash content of the sample.
All masses were converted to a percentage of ash-free dry mass remaining.

Soil Respiration: A laboratory incubation experiment was set up to measure CO2 flux as
described previously (A. S. Grandy & Robertson, 2007). Approximately 20 g of air dried soil was
weighed into 60 ml serum vials and 5 g water was added to adjust the moisture content to 60 %
of the water holding capacity. The vials were tightly capped with rubber septa. Water was
added as needed during the incubation period of 125 d to keep the moisture levels constant.
On each sampling date all the vials were uncapped for approximately 30 min to allow for air
exchange and then capped again. A volume of 0.5 ml was drawn with a syringe from the vials at
zero, thirty and sixty min interval, immediately after recapping with the septa and analyzed
with an infrared gas Analyzer, (LI.820) for the CO2 content. The process was repeated over 46 d
with a greater sampling intensity in the beginning of the 125 d incubation period. The CO2 flux
was calculated as described in Robertson et al. (1999) and reported as µg CO2-C/g soil/d
28

Density Fractionation: Light fraction organic matter (LF) was separated from the soil by the
density fractionation method as described in Robertson et al. (1999). A sub-sample of 20 g airdried soil was taken into centrifuge tube and mixed with 200 ml of sodium polytungstate (NaPT)
3

solution of 1.7 g/cm density. To separate the LF from the HF the suspension was dispersed by
shaking with a shaker for 30 min and then centrifuged (Sorvall RC-5B) for 20 min at 5000
rev/min. A vacuum source was used to collect the suspended LF, avoiding disturbance of the
heavy fraction. The LF was washed with 400 ml of DI water to remove any residual NaPT, and
weighed after drying at 105°C, and ground for further analysis.

Litter Molecular Chemistry: The molecular chemistry of litter was assessed by pyrolysis gas
chromatography/mass spectroscopy following the procedures outlined in Grandy et al. (2007).
Briefly, pulverized litter was pulse-pyrolyzed in quartz tubes on a Pyroprobe 5150 (CDS
Analytical Inc., Oxford PA) using a pyrolysis temperature of 600°C. Pyrolized samples were
transferred onto a gas chromatograph (Trace GC Ultra, Thermo Scientific) where they were
further separated by passing through a heated, fused silica capillary column (60m x 0.25mm
i.d.). GC oven temperature was increased from 40 to 270 °C at a rate of 5°C per minute with a
final temperature ramp to 310°C (30°C per min). Finally, compounds were transferred to a
mass spectrometer (Polaris Q, Thermo Scientific) via a 270°C heated transfer line where they
were ionized by a heated source (200°C) and detected. The identification of compounds
involved the analysis of total ion chromatogram on which the abundance of all ions is scaled

29

relative to the largest peak.

Peaks were identified using Automated Mass Spectral

Deconvolution and Identification (AMDIS V 2.65) as well as the National Institute of Standards
and Technology library (NIST). While this method does not provide quantitative assessment of
compounds it does allow for the comparison of the relative molecular composition of
substrates.
Chemically labile SOM (CLOM): The chemically labile SOM was measured as described by Weil
et al. (2003). A 0.2M KMnO4 stalk solution was prepared and its pH was adjusted to 7.2 by
adding a drop of 0.1 N NaOH. Four standard concentrations (0.005, 0.01, 0.015, and 0.02M )
were also prepared from the 0.2M KMnO4 stock solution and then diluted to working
concentrations (0.00005, 0.0001, 0.00015, 0.0002M). A 5.0g air-dried soil sample, 18ml of
deionized water and 2.0ml of 0.2M KMnO4 were put in centrifuge tubes. A soil standard of 5.0g
of known pulverized soil and ‘solution standard’ (i.e no soil) were also prepared and processed
in similar manner. These serve as a quality control reference. All the centrifuge tubes were
shaken at 240 rpm for 15 min at room temperature. The samples were then placed in a dark
area and allowed to settle for ten minutes. Meanwhile, 49.5 ml of deionized water was added
in another centrifuge tube along with 0.5ml of the supernatant. This solution was inverted to
mix properly and was used in a 96-well plate reading spectrophotometer to read the amount of
C oxidized as a function of the quantity of permanganate reduced. The CLOM values were
reported as mg of oxidizable carbon per kg of soil, following equation was used to determine
CLOM:

30

-1

CLOM (mg kg ) =

[0.02 mol/ L - (a + b × Abs)] × (9000 mg C/ mol) × (0.02 L solution/ Z)
Where: 0.02 mol/L = initial solution concentration
a = intercept of the standard curve
b = slope of the standard curve
Z = absorbance of unknown

9000 = milligrams of carbon oxidized by 1 mole of MnO4 changing from Mn

7+

 Mn

2+

0.02 L = volume of stock solution reacted
Z = weight of air-dried soil sample in k
Statistical analysis: The experimental design for this study was a randomized complete block
design (RCBD). It had a single factor, N fertilizer, with three levels (0, 134 and 291Kg N/ha),
replicated four times. The data analysis for soil and litter variables was conducted in PROC
MIXED (SAS Institute Inc, 2002). Normality of the residuals was checked using normal
probability and box plots. Data were transformed where deviations from normality were
observed. The homogeneity of variances was checked using Levene’s test. For soil variables
(enzymes, LF, Inorganic N, CLOM) the data was analyzed with the REPEATED statement in the
PROC MIXED. Variance-covariance structure for the repeated measures was selected on AIC
and BIC criteria. The results are reported statistically significant at α=0.05.

31

RESULTS
Litter Enzymes: There was a higher enzyme activity on litter in comparison to soil (Figures.9, 10,
11 & 12). Among the two types of litter; the activity was higher on corn than wheat. Except for
CBH where there was a marginal significant effect of N (P=0.05) and a significant nitrogen by
time interaction (P=0.02), none of the litter enzymes namely, BG, NAG, and POX, showed a
response to the N treatment (Table.6) The CBH activity was significantly different between the
two types of litter (P=0.02) being higher (28%) on corn in comparison to wheat litter. The
activity of BG, NAG and POX were 19.2%, 3.4%, 15.2% higher, respectively, on corn than on
wheat, but none of these differences were significant between the two types of litter.
Mass Loss: There was no N effect on litter decomposition rates (Figure:4 ) on either type of
litter but there were significant differences between the corn and wheat litters with greater
mass loss (73% mass loss) in corn than in the wheat litter (63% mass loss). There was a
significant litter*time effect (Table.6).
Litter Chemistry: The corn and wheat litters were analyzed two times for their chemical nature
(Table.3). The first analysis was in June 2008 before the litter was placed into the experimental
plots and then at the end of the experiment, in Sept 2009. I found no significant differences
between the 0N and the 291N litter treatments in all the chemical compounds in the corn as
well as the wheat litter. The relative abundance of lignin, lipid, and N-bearing compounds when
averaged across the N treatment and compared between the two types of litter were found 56,
350 and 10 % higher respectively in wheat than in corn litter where as phenols and
polysaccharides were 25 and 63% higher respectively in corn than in wheat.
32

Light Fraction Organic matter (LF): The light fraction (mg/g soil) increased by 22% in June in the
291N plots in comparison to 0N, but decreased by 14% in Aug but both the differences being
not significant (Table.4). The C concentration (mg/g of LF) of the LF organic matter increased by
8% in June and 1.6% in Aug in the high N treatment in comparison to 0N, similarly the N
concentration (mg/g of LF) increased by 16% in June and by 8% in Aug under 291KgN/ha
treatment in comparison to 0N (Table:4). Also, there were no significant differences in the LF-C
and LF-N (mg/g soil) in soil. The only significant increase (P = 0.04) in LF (mg/g soil) was in June
by 3.9% in 134N in comparison to 0N. Also the LF decreased by 9.7% in 291N plot in Jun and
17% in Aug in comparison to 134N plots but the differences being not significant. The LF in soil
(mg/g soil) increased by 178% (P = <.0001) from Aug to Jun in 0N plots, 112% (P= 0.0003) in
134N plots and 94% (P = 0.0012) in 291N plots.
Soil Enzymes: The activity of the soil enzymes decreased in high N plots in comparison to 0N
plots, as for BG (Figure.8), CBH (Figure.6), and NAG (Figure.5), there was 14.5, 21.8, and 17.8 %
decrease in the activity respectively, but none of these differences being significant at (α =0.05)
between 0 and high N. However POX activity (Figure.) in soil increased (8.8%) under high N but
the differences were not significant (Table.7). The overall activity for POX peaked in the early
time steps and then declined with time showing no significant differences except for the month
of Oct when there was a higher (66% increase) activity (P=0.01) under the high N treatment.

Soil Respiration: The soil CO2-C emission (Figure: 2) during the laboratory incubations showed a
significant decrease (P=0.0001) in the CO2 flux in the soils treated with high N and this trend

33

was persistent in all the time steps. The CO2 flux decreased significantly by 41.2% in the high N
plots in comparison to the 0N plots in June, 54.5% in July 53.8% Aug, and 37.2% in the month of
September. Also there was a significant time effect (Table.7).
Chemically Labile Organic matter (CLOM): There were no significant differences in the CLOM. I
did not observe any N effect between the 0 and the high N treatments also there was no time
effect (Table: 7).

Inorganic N: The inorganic NH4 and NO2 + NO3 (Table:5) showed a significant nitrogen and time
interaction with 378.8 and 296.7% increase in the soil concentrations averaged across all time
steps, under high N. All of the variables showed significant time effect.

34

DISCUSSION
To understand the main concept behind this experiment, I propose a conceptual model
for my study (Figure:1). This model highlights the importance of litter, litter tissue chemistry
and soil microbial activity in decomposition dynamics and soil C sequestration. This model
summaries all the steps and events from the application of N fertilizer to the litter and/or soil,
the possible changes in the soil microbial activity in the form of enzyme activity, the effects on
the rates of decomposition of two chemically different litter types to the release of soil C as
CO2. This study also explores the possibility of the aforementioned changes in the above
ground litter being translated into the below ground LF and eventually either its contribution in
to the soil organic carbon pool, its direct effects of the added inorganic N on the soil microbial
activity as well as the indirect effects on the microbial activity through changes in the above
ground biomass (Figure:1).
Litter Dynamics: In general, it has been established that N fertilization increases decomposition
of litter with relatively low lignin content and decreases or has no effect on mass loss of
residues with high lignin content (Waldrop et al. 2004; Knorr et al. 2005). The different
responses to N enrichment based on litter quality have been clearly demonstrated in the
Manistee National Forest, MI.

Here, Waldrop et al. (2004) showed accelerated litter

decomposition in a sugar maple basswood forest with relatively low concentrations of lignin
derivatives but in a black oak white oak forest higher litter lignin concentrations controlled
decomposition dynamics. Multiple studies have sought to understand the biological basis for
these changes (Saiya-Cork et al., 2002; Waldrop et al., 2004aa).
35

N-Fertilization

Litter

Enzymes

Mass Loss

Litter Chemistry

Light Fraction

Enzymes

Soil
CLOM

Respiration

Figure: 1 A conceptual model showing direct and/or indirect effects of the inorganic
fertilizer-N and the subsequent effect on litter and soil C cycling processes.
CLOM: chemically labile organic matter.

36

As long ago as 1927, Waksman and Tenney suggested that inorganic N accelerated the
decomposition of crop residues.

A handful of subsequent studies also suggested that

supplemental inorganic N can stimulate the breakdown of residues with high C/N ratio (Recous
et al., 1995). Waksman’s studies along with those of Recous et al. (1995) show that under some
conditions N fertilization increases litter decomposition rates, which will reduce soil C storage.
Indeed, many no-till producers have adopted the idea that N accelerates decomposition and
now use inorganic N applications to reduce their surface residues.

Evidence suggests that N alters microbial decomposition by differentially affecting
degradation of polysaccharides and polyphenols, resulting in an uncoupling of these processes
(DeForest et al., 2004; Sinsabaugh et al., 2003). High N levels stimulate hydrolase enzymes that
break down carbohydrates, resulting in accelerated decomposition of organic materials rich in
labile C compounds. In contrast, phenol oxidase and peroxidases are suppressed by high N
availability, which reduces decomposition of litter or SOM with high concentrations of lignin
and its derivatives and other secondary compounds (Sinsabaugh et al., 2005; Sinsabaugh et al.,
2004).
The chemical composition of plant biomass impacts decomposition. For a net increase in
SOC the C inputs must exceed the CO2 flux. On a global scale climate is the best predictor of
rate of decomposition where as on a climatic scale biomass chemistry is the best predictor. As
mentioned above many studies have reported an inhibitive effect of lignin on decomposition
rate. I used two types of litter with a different chemical composition.

37

Litter quality may act alone or in concert with other factors, including the form of N or N
rate, to influence the transfer of plant-derived C into different SOM pools (Bradford et al. 2008).
To check this assumption I measured the chemical composition of litter and the rate of mass
loss and the enzyme activity on litter. Before decomposition, the relative abundance of lignin
(Table: 3) was 20% in corn and 28% in wheat, which increased to 35% and 54% in corn and
wheat, respectively, after decomposition, whereas the relative abundance of polysaccharides
was 38% in corn and 22% in wheat which increased to 43% and 16% in corn and wheat
respectively after decomposition. The relative abundance of lignin, lipid, and N-bearing
compounds when compared between the two types of litter were 56, 350 and 10% higher in
wheat than in corn litter, respectively, whereas phenols and polysaccharides were 25 and 63%
higher in corn than in wheat respectively. There was >50% mass loss in both types of litters.
(Figure.4) Thus, in this study the litter being examined had very different chemical
characteristics; the wheat possessing significantly higher chemical recalcitrance than the corn. I
anticipated that because of the differences in chemistry, N enrichment would suppress
decomposition in wheat and have positive or no effect on decomposition in corn. However, I
did not detect any effects of N on total mass loss (Figure.4) in either litter type, and litter
enzymes either did not respond to N, or exhibited modest decreases in activity due to N
fertilization (CBH and BG) at the June time point only (Figure.6 & 8). As anticipated that more
recalcitrant litter i.e. with higher lignin content would show a decreased decomposition rate
with higher N application rates, my data did not show response to the N addition with no
significant correlations among litter enzymes and lignin and polysaccharides (Table.9)

38

Nonetheless I observed higher enzyme activity on corn than on wheat litter, and a greater mass
loss in corn (73% mass loss) than in wheat (63% mass loss) litter.

Soil Processes: In this study, fertilized soils had higher LF and total C concentrations,
although the differences not being significant but we see a trend (Table: 4). This is similar to the
findings of Gregorich et al. (1996) who used natural abundance methods to demonstrate that
the half-life of corn-derived C in a continuous corn cropping systems was the same irrespective
of N fertilization rate. The authors concluded that fertilization increases crop residue
production, without accelerating its decomposition rate, resulting in SOM increases.

Many

other studies have shown that N fertilization increases SOM content by increasing crop residue
inputs (e.g Sainju et al. 2006; Christopher and Lal, 2007; Kaur et al. 2008; Banger et al. 2010).
Although these studies did not measure litter decomposition, per se, they do indicate that
increased residue inputs are not offset by potential increases in litter decomposition rates,
resulting in increased SOM concentrations. I acknowledge that short-term, process-level studies
may not always reflect long-term dynamics, and future efforts to understand N effects on
decomposition and SOM dynamics need to encompass a range of temporal and spatial scales.
Nonetheless, when the results of this study are interpreted along with others examinining longterm soil C responses to N fertilizer use (e.g. Gregorich et al., 1996; Banger et al., 2010), there is
little evidence that N fertilizer induced changes in soil biological processes, per se, will
accelerate litter decomposition in corn-based cropping systems.

The highest rate of N fertilization reduced CO2 flux in an incubation assay, (Figure.2) by
46.9% (P = 0.0001) compared to the unfertilized treatment. Incubations are widely thought to

39

provide insight into the labile or ‘active’ soil C pool that is readily available to soil microbes and
has a short turnover time. In my study I evaluated other indicators of labile SOM pools, notably
light fraction carbon, and permanganate oxidizable carbon pool. In contrast to the laboratoryassessed respiration rates, I did not observe any decrease in light fraction or chemically
oxidizable carbon with nitrogen fertilization. In contrast to CO 2 mineralization response, N
fertilization was associated with increased LF-C concentrations and LF-N content (Table.4)
compared to the unfertilized treatment, and there were no effects of fertilization on CLOM
(Figure.3). Thus, the consistent declines in soil respiration that we measured may be due to
changes in soil properties other than available C, including differences in decomposer
communities or microbial biomass resulting from N fertilization.
In recent years, laboratory incubations such as the ones I conducted here have come
under scrutiny for ignoring differences in the structure and function of decomposer
communities. That is, differences in short-term laboratory CO2 flux may be a function of the
resident microbial communities, their metabolic capabilities, and substrate preferences, as well
as organic matter quality and quantity. It is thus possible that microbial-level differences
among N treatments explain the observed variation in potential respiration rates. Other
studies have shown that high levels of inorganic N can suppress microbial activity (Al-Kaisi et al.,
2008; Bowden et al., 2004; Clark et al., 2009; Fog, 1988; Wilson & Al-Kaisi, 2008). These
changes in microbial activity may be related to declines in microbial biomass with N
fertilization, which have been frequently reported. For example, in a meta analysis including 82
studies, Treseder et al. (2008) reported that microbial biomass declined by an average of 15%
40

following N fertilization, and declines in soil respiration rates were correlated with these
changes in soil microbial biomass. In another synthesis, Liu and Greaver (2010) found that N
addition reduced microbial biomass C by 20% and microbial respiration rates by 8%.
Changes in decomposer community composition could also help explain the observed
effects of N fertilizer on soil respiration rates. Recent research suggests that decomposer
community composition could regulate decomposition dynamics because of variation in
substrate preferences among microbial communities (Balser and Firestone 2005; Osler and
Sommerkorn 2007; Valaskova et al. 2007; Strickland et al. 2009). However, soil decomposer
communities could have an additional – albeit indirect – effect on soil respiration rates by
altering the chemistry of SOM. Soil organic matter biochemistry is related to its recalcitrance
and decomposition rate and also to its ability to be protected from microbial attack by
interactions with soil minerals (Grandy & Neff, 2008). The importance of organic matter
chemistry in decomposition has been shown in empirical studies (Grandy, Strickland, et al.,
2009) and is widely acknowledged in quantitative and conceptual models of the process
(Grandy & Neff, 2008; Sollins et al., 1996). However, decomposition models currently focus on
initial litter chemistry and do not consider the possibility that situ changes in litter chemistry
during decomposition could substantially change decomposition dynamics.

Further, most

conceptual models describing changes in litter and SOM chemistry during decomposition
suggest consistent, predictable changes in chemistry based on the extent of mass loss and do
not explicitly consider the possibility that chemical changes in SOM during decomposition might
follow multiple trajectories depending on decomposer community characteristics. However,
Wickings et al. (2009) demonstrated that decomposer communities can strongly influence
41

changes in SOM chemistry during decomposition. Thus, an alternative explanation for the
differences in SOM chemistry we observed is that N influenced soil communities and thereby
altered the chemistry of SOM and its decomposition rate. However, we saw few changes in the
chemistry of litter or LF pools No effect of N was observed in terms of litter biochemical
composition at the end of the decomposition time period.
Thus, either N had no effect on litter chemistry, or effects were limited to pools that we
did not measure. Although more effort is needed to understand the declines in soil respiration
that are reported here and elsewhere (e.g.Treseder et al. 2007; Martinez et al. 2010), we found
little evidence that these declines were associated with changes in SOM pool sizes or tissue
chemistry. More likely, changes in microbial biomass, perhaps coupled with changes in
microbial community structure, altered respiration rates following N fertilization.

42

CONCLUSION
Following are several alternative explanations for the results that could not be addressed:
a)

However, N fertilizer rate may have effects on decomposition dynamics and long-term

soil C balance that we did not consider. First, N fertilization rate has been shown to influence
the C/N ratio of crop residues (Lee & Bray, 1949). Litter C/N ratio is one of the primary drivers
of initial litter decomposition rates (Aber & Melillo, 1982), and declines in C/N ratio with
increasing N availability may accelerate decomposition dynamics. Because our study focused
on soil biological processes as a driver of decomposition, we used only one type of corn litter
and one type of wheat litter, which allowed us to test differences in mass loss of a common
species due to differences in decomposer communities, but not among litter types containing
different C/N ratios.
b)

Second, N fertilization might influence the allocation of resources above and

belowground (Johnson, 1985; Liu & Greaver, 2010). Recent evidence points to the selective
preservation of root structures in soil (Bird & Torn, 2006; Bontti et al., 2009). This is likely
because of their unique chemistry as well as their intimate association with minerals. Liu and
Greaver (2010) found that N addition increased aboveground litter inputs by ~ 20% but did not
increase fine root inputs. Although evidence for such an effect is inconclusive, N fertilization
could influence soil C dynamics through altering root to shoot ratios.
c)

Third, N can have an effect on stable SOM pools and long-term SOM dynamics that

short-term litter decomposition studies will not identify.

Studies have suggested that N

fertilization may influence the complex biochemical reactions that lead to chemical
43

recalcitrance of SOM (Neff et al., 2002). Plant biomass, the primary source of bulk soil organic
matter, consists of heterogeneous, primarily polymeric molecules with a wide range of turnover
times (Trinsoutrot et al., 2000).

These compounds undergo microbial degradation and

transformation, catalyzed by multiple enzyme systems, and many participate in secondary
reactions, e.g. Maillard product formation (Jokic et al., 2004).

N may influence these

transformations by directly influencing chemical reactions involving SOM. N is an important
component of humic substances and may directly catalyze or at least participate in humification
reactions and play an important role in the formation of precursors involved in stabilization
reactions (Haider et al., 2004). Additionally, it has been demonstrated that lignin materials and
tannins in the presence of N can undergo oxidation and form heterocyclic N-containing
compounds that are inhibitory to microorganisms (Skene et al., 1997).

44

Lignin

Lipid

Phenols

KgN/ha

Corn

na
0
291

0.2
0.01
0.1
0.33(0.067) 0.01(0.005) 0.02(0.101)
0.36(0.067) 0.01(0.005) 0.02 (0.101)

Wheat

na
0
291

Polysaccharide N-bearing Unknowns
(Relative Abundance)

0.28
0.16
0.07
0.59(0.62) 0.036(0.02) 0.01(0.03)
0.49(0.06)0.05(0.01) 0.016(0.02)

L:N

L:P

0.38
0.03
0.27
6.4
0.51
0.422(0.04) 0.052(0.002) 0.142(0.016) 6.75 (1.46) 0.86 (0.24)
0.43(0.04) 0.05 (0.002) 0.13 (0.016) 7.16 (1.46) 0.91 (0.24)
0.22
0.15(0.03)
0.17(0.03)

0.09
0.05(2.73)
0.06(2.47)

0.18
3.2
1.27
0.16(0.03) 12.18(2.6) 4.1(0.86)
0.2(0.02) 8.24(2.6) 3.13(0.80)

ANOVA
N
0.44
0.314
0.65
0.76
0.1
0.65
0.16
0.28
Ltr
0.0001
0.005
0.0001
0.001
0.0001
0.0001
0.0001
0.0002
N*Ltr
0.02
0.08
0.46
0.58
0.12
0.04
0.001
0.19
Table 3: Litter Chemistry: Relative abundance of chemical compounds in Corn and wheat litters, measured in the beginning
of the experiment (June, 2008) and at the end (June, 2009). Where N = effect of Nitrogen, Ltr = effect of Litter and
N*Ltr = Nitrogen and Litter effect, na =the initial litter chemistry not subject to the three (0,134,294 Kg/ha) N treatments.

45

LF
C
KgN/ha mg/g soil mg/g LF

N
LF-C
LF-N
mg/g LF mg/g soil mg/g soil

C:N
ratio

Jun

0 1.66(0.12) 235(13.47) 12(0.70) 0.39(0.02) 0.02(0.00) 19(0.01)
134 2.26(0.38) 254(17.35) 13(0.70) 0.57(0.10) 0.03(0.00) 18(0.96)
291 2.04(0.07) 254(7.89) 14(0.40) 0.55(0.01) 0.03(0.00) 18(0.00)

Aug

0 4.62(0.53) 242(12.11) 12(1.10) 1.12(0.16) 0.06(0.00) 20(1.74)
134 4.80(0.19) 208(4.062) 11(1.10) 1.00(0.04) 0.05(0.00) 18(0.17)
291 3.96(0.08) 246(11.06) 13(0.23) 0.97(0.05) 0.05(0.00) 18(0.77)

ANOVA

N
0.16
0.056 0.069
0.325
0.194 0.438
T
<.0001
0.026
0.07
<.0001
<.0001 0.989
N*T
0.14
0.083 0.211
0.074
0.126 0.918
Table 4: Light Fraction organic matter and C, N content per grams of soil and C: N ratios,
measured in Jun and Aug 2008, where N = effect of Nitrogen, and T= effect of time and
N*T= effect of Nitrogen by Time.

46

Jun

NH4

(NO3+NO2)

KgN/ha
0 3.14(0.34)
134 5.01(0.93)
291 5.01(0.97)
0
134
291

Jul

Aug
(µg/g)

Sept

2.02(0.01) 3.61(0.53) 3.9(0.56)
24.03(8.01) 2.7(0.26) 3.67(0.06)
79.6(5.72) 5.72(1.46) 3.28(0.03)

Oct

Nov

4.04(0.55) 4.06(0.22)
3.94(0.78) 3.24(0.38)
3.72(0.33) 2.99(0.45)

7.04(1.41) 2.22(0.44) 3.33(0.31) 2.73(2.9)
2.9(0.07) 4.07(0.13)
16.73(4.34) 16.81(3.75) 3.24(0.14) 3.07(3.11) 3.11(0.22) 4.44(0.19)
18.61(3.36) 24.94(2.96) 24.76(7.91) 10.14(0.43) 3.55(0.21) 6.43(0.65)

Table 5: Inorganic NH4 and NO3+NO2. ANOVA results consistent with significant Nitrogen and
Time interaction.

47

CBH

NAG

POX

(µmol/h/g)

KgN/ha
Corn

BG

AFDM
(%)

0.57(0.08)

1.95(0.32) 0.94(0.22)

1.19(0.29)

0.54(0.04)

134

0.97(0.21)

3.17(0.78) 1.23(0.31)

1.36(0.28)

0.53(0.02)

291

0.85(0.13)

2.79(0.56) 1.14(0.22)

1.66(0.31)

0.53(0.03)

0.4(0.19)

1.67(0.28) 0.85(0.12)

1.2(0.21)

0.630.04)

134

0.64(0.17)

2.16(0.64) 1.16(0.32)

1.1(0.26)

0.65(0.02)

291

Wheat

0

0.68(0.003)

2.47(0.5) 1.18(0.32)

1.36(0.32)

0.64(0.05)

0

ANOVA
N
0.05
0.07
0.15
0.24
0.95
Ltr
0.02
0.06
0.81
0.16
<0.0001
N*Ltr
0.89
0.46
0.91
0.64
0.062
Time
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
N*Time
0.02
0.05
0.36
0.14
0.23
Ltr*Time
0.71
0.83
0.23
0.98
<0.0001
N*Ltr*Time
0.47
0.65
0.26
0.13
0.89
Table 6: ANOVA of corn and wheat litter enzymes and Mass loss rates. Where
CBH = β-D-cellobiohydrolase, BG = β-glucosidase, NAG = N-acetyl-β-D-glucosidase and
POX = Phenol Oxidase. AFDM= Ash free dry mass, N = effect of Nitrogen treatment,
Ltr = effect due to litter type.

48

CBH
KgN/ha
0
134

BG

NAG

POX

CO2

CLOM

(µmol/h/g)
(µg CO 2-C/g/d) (mg/Kg)
0.06(0.01) 0.2(0.03) 0.06(0.01) 1.33(0.53)
252.2(126.1) 494.51(27.53)
0.06(0.005) 0.19(0.03) 0.06(0.01) 1.22(0.51)

176.2(88.1) 488.52(9.67)

291

0.05(0.003) 0.17(0.01) 0.05(0.01) 1.45(0.48)
178(89.1) 455.70(18.24)
ANOVA
T
T
T
T
N,T
NS
Table 7: ANOVA of soil variables with averages and standard errors in parentheses: Where
CBH = β-D-cellobiohydrolase, BG = β-glucosidase, NAG = N-acetyl-β-D-glucosidase and

POX = Phenol Oxidase. CO2 = Cumulative CO2 flux from soil lab incubations for 125 days. N = significant
effect of Nitrogen, T = significant effect of time, N*T = interaction effect of Nitrogen and time,
NS = Non significant.

49

Pearson Correlation Coeffcients
NAG
CBH
BG POX
(Soil)
Corn
N-acetyl-β-D-glucosidase
β-D-cellobiohydrolase
β-glucosidase
Phenol oxidase

0.38
0.17
0.65
-0.003

0.17
-0.01
0.04
-0.16

0.16 0.29
-0.03 0.02
0.02
0
0.16 0.12

Wheat
N-acetyl-β-D-glucosidase
0.42
0.13
0.15 0.55
β-D-cellobiohydrolase
0.17
0.03
0.02 0.1
β-glucosidase
0.22
0.07
0.07 0.05
Phenol oxidase
-0.01 -0.12 -0.17 0.06
Table 8: Correlations between soil and corn and wheat litter enzymes.
Correlation coefficients in bold are significant (P<=0.05). Abbreviations:
NAG (N-acetyl-β-D-glucosidase), CBH (β-D-cellobiohydrolase),
BG (β-glucosidase),POX (Phenol Oxidase).

50

Lignin Poly
Corn
β-glucosidase
Phenol oxidase
β-D-cellobiohydrolase
N-acetyl-β-D-glucosidase

-0.64 0.67
0.22 -0.28
-0.64 0.65
0.14 -0.14

Pearson Correlation Coeffcients
Phenols Lipids N-bearing Unknowns
Relative Abundance
0.71 0.16
0.74
0.5
-0.32
-0.1
-0.44
-0.2
0.81 0.36
0.8
0.53
-0.15
-0.5
0.015
-0.24

L:N

L:P

-0.68 -0.66
0.25 0.17
-0.69 -0.62
0.12 0.08

Wheat
β-glucosidase
-0.67 0.67
0.67 0.71
0.64
0.62 -0.58 -0.64
phenol oxidase
0.41 -0.12
-0.56 -0.54
-0.51
-0.26 0.38 0.17
β-D-cellobiohydrolase
-0.29 0.46
0.26 0.32
0.26
0.3 -0.19 -0.39
N-acetyl-β-D-glucosidase
-0.63 0.42
0.8 0.87
0.75
0.36 -0.56 -0.44
Table 9: Correlations between litter enzymes and the relative abundance of chemical classes in litter.
Correlation coefficient in bold are significant (P = 0.05).Compound abbreviations: Lip (Lipids),
Poly(Polysaccharides), N-bearing (Nitrogen bearing compounds).

51

1800
0N
134N

(µg CO2 -C/g soil)

Cumulative CO2

1500

291N

1200

900

600

300

0
June

July

Aug

Sept

Figure 2: Carbon mineralization monitored in a field study of corn nitrogen response at the W.K. Kellogg Biological Station,
Hickory corners, MI. Reported here as cumulative soil CO2 emission from laboratory incubation of soil samples over 125
days. Samples were collected on June 17, July 09, August 05 and September 3rd of 2008. Analysis of variance (ANOVA)
indicated a significant N rate effect (P = 0.0001).

52

750
0N
120N

600

CLOM
(mg/Kg)

291N

450

300

150

0
july

Aug

Sept

Figure 3: Chemically labile organic matter (CLOM) monitored over the summer of (2008) in a field study of
nitrogen response at the W.K. Kellogg Biological Station, Hickory Corners, MI. Three levels of nitrogen fertilizer
were compared, 0, 134 kg N/ha and 291 kg N/ha.

53

1.2

Wheat

Corn

0N
134KgN
291KgN

Ash Free Dry Mass
(%)

1
0.8
0.6
0.4
0.2
0
June'08

July'08

Aug'08

Sep'08

May'09

Jun'09

June'08

July'08

Aug'08

Sep'08

May'09

Jun'09

Figure 4: Effect of 0, 134 and 291kgN/ha on decomposition rates of wheat litter at the W.K. Kellogg Biological Station,
Hickory corners, MI. ANOVA suggested significant differences (P = <0.0001) between the litter types with higher mass
remaining in wheat than in Corn litter.

54

0.12

N-acetyl-β-D-glucosidase
0N

Enzyme Activity
(µmol/h/g)

0.1

134N

0.08

291N

0.06
0.04
0.02
0

June

July

Sep

Oct

Figure 5: Activity of N-acetyl-β-D-glucosidase (NAG) in soil, showing significant time
effect only under three levels (0, 134 and 291 KgN/ha) of N fertilizer treatment
measured from Jun’08 to Oct’08 at W.K. Kellogg Biological Station, Hickory corners, MI.

0.1

β-D-1,4-cellobiosidase

Enzyme Activity
(µmol/h/g)

0.08

0N
134N
291N

0.06
0.04
0.02
0
June

July

Sep

Oct

Figure 6: Activity of β-D-1,4-cellobiosidase (CBH) in soil under three levels
(0, 134 and 291KgN/ha) of N fertilizer rate measured from Jun’08 to Oct’08 at W.K.
Kellogg Biological Station, Hickory corners, MI, with significant time effect only.

55

3

Phenol Oxidase
0N
134N
291N

Enzyme Activity
(µmol/h/g)

2.4
1.8
1.2
0.6

0
June

July

Sep

Oct

Figure 7: Activity of Phenol Oxidase (POX) in soil under three levels
(0, 134 and 291KgN/ha) of N fertilizer rate measured from Jun’08 to Oct’08 at
W.K. Kellogg Biological Station, Hickory corners, MI,with significant time effect
only.

β-1,4-glucosidase

0.3

0N
Enzyme Activity
(µmol/h/g)

0.25

134N

0.2

291N

0.15
0.1

0.05
0
June

July

Sep

Oct

Figure 8: Activity of β-1,4-glucosidase (BG)in soil under three levels
(0, 134 and 291KgN/ha) of N fertilizer rate measured from Jun’08 to Oct’08 at
W.K. Kellogg Biological Station, Hickory corners, MI with significant time effect
only.

56

6

Corn
β-1,4-glucosidase

Wheat
β-1,4-glucosidase

0N
134N
291N

Enzyme Activity
(µmol/h/g)

5
4
3
2
1
0
july'08 Aug'08 Sep'08

Sep'08 May'09 June'09

Jul'08

Aug'08

Sep'08

Sep'08

May'09

June'09

Figure 9: Activity of β-1,4-glucosidase(BG) on wheat and Corn litters under three levels of Inorganic Nitrogen Fertilizer
(0, 134, 291Kg/ha), measured over a period of one year from Jun’08 to Jun’09 W.K. Kellogg Biological Station,
Hickory corners, MI. ANOVA suggested a significant N by time interaction (P = 0.05).

57

6

Wheat
β-D-1,4-cellobiosidase

Corn
β-D-1,4-cellobiosidase
0N
134N
291N

Enzyme Activity
(µmol/h/g)

5
4
3
2
1
0
july'08

Aug'08

Sep'08

Sep'08

May'09

June'09

Jul'08

Aug'08

Sep'08

Sep'08

May'09

June'09

Figure 10: Activity of β-D-1, 4-cellobiosidase(CBH) on wheat and Corn litters under three levels of Inorganic Nitrogen
Fertilizer (0, 134, 291Kg/ha), measured over a period of one year from Jun,08 to Jun’09 at W.K. Kellogg Biological Station,
Hickory corners, MI.

58

Corn
N-acetyl-β-D-glucosidase

Wheat
N-acetyl-β-D-glucosidase

6

Enzyme Activity
(µmol/h/g)

5

0N
134N
291N

4
3
2
1
0
july'08

Aug'08

Sep'08

Sep'08

May'09

Jul'08

June'09

Aug'08

Sep'08

Sep'08

May'09

June'09

Figure 11: Activity of N-acetyl-β-D-glucosidase on wheat and Corn litters under the effect of N fertilizer treatment (0, 134,
291Kg/ha), measured over a period of one Year from Jun’08 to Jun’09 at W.K. Kellogg Biological Station, Hickory Corners, MI.

59

6

Corn
Phenol Oxidase

Wheat
Phenol Oxidase

0N
134N
291N

Enzyme Activity
(µmol/h/g)

5
4
3
2

1
0
july'08

Aug'08

Sep'08

Sep'08

May'09

June'09

Jul'08

Aug'08

Sep'08

Sep'08

May'09

June'09

Figure 12: Activity of phenol oxidase on wheat and corn litters measured over a period of one year from Jun’08 to Jun’09
under the influence of N fertilizer treatment (0, 134, 291Kg N/ha) at W.K. Kellogg Biological Station, Hickory Corners, MI

60

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