nitrogen alters microbial enzyme dynamics but not lignin ... publications/2016...soil mineral n is...
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Nitrogen alters microbial enzyme dynamics but not ligninchemistry during maize decomposition
Zachary L. Rinkes . Isabelle Bertrand . Bilal Ahmad Zafar Amin .
A. Stuart Grandy . Kyle Wickings . Michael N. Weintraub
Received: 29 September 2015 / Accepted: 10 March 2016 / Published online: 25 March 2016
� Springer International Publishing Switzerland 2016
Abstract Increases in nitrogen (N) availability
reduce decay rates of highly lignified plant litter.
Although microbial responses to N addition are well
documented, the chemical mechanisms that may give
rise to this inhibitory effect remain unclear. Here, we
ask: Why does increased N availability inhibit lignin
decomposition? We hypothesized that either (1)
decomposers degrade lignin to obtain N and stop
producing lignin-degrading enzymes if mineral N is
available, or (2) chemical reactions between lignin and
mineral N decrease the quality of lignin and limit the
ability of decomposers to break it down. In order to
test these hypotheses, we tracked changes in carbon
(C) mineralization, microbial biomass and enzyme
activities, litter chemistry, and lignin monomer con-
centrations over a 478-day laboratory incubation of
three maize genotypes differing in lignin quality and
quantity (F292bm3 (high lignin)\F2 (mediumlignin)\ F2bm1 (low lignin)). Maize stem internodesof each genotype were mixed with either an acidic or
neutral pH sandy soil, both with and without added N.
Nitrogen addition reduced Cmineralization, microbial
biomass, and lignin-degrading enzyme activities
across most treatments. These dynamics may be due
to suppressed fungal growth and reduced microbial
Responsible Editor: Susan E. Crow.
Electronic supplementary material The online version ofthis article (doi:10.1007/s10533-016-0201-0) contains supple-mentary material, which is available to authorized users.
Z. L. Rinkes (&) � M. N. WeintraubDepartment of Environmental Sciences, University of
Toledo, Toledo, OH 43606, USA
e-mail: [email protected]
I. Bertrand � B. A. Z. AminINRA, UMR614 FARE, esplanade Roland Garros,
51100 Reims, France
A. S. Grandy
Department of Natural Resources and the Environment,
University of New Hampshire, Durham, NH 03824, USA
K. Wickings
Department of Entomology, Cornell University, New
York State Agricultural Experiment Station, Geneva,
NY 14456, USA
Present Address:
I. Bertrand
INRA UMR Eco&Sols, place P Viala, 34060 Montpellier,
France
B. A. Z. Amin
Department of Environmental Sciences, COMSATS,
CIIT, Abbottabad, Pakistan
123
Biogeochemistry (2016) 128:171–186
DOI 10.1007/s10533-016-0201-0
http://dx.doi.org/10.1007/s10533-016-0201-0http://crossmark.crossref.org/dialog/?doi=10.1007/s10533-016-0201-0&domain=pdfhttp://crossmark.crossref.org/dialog/?doi=10.1007/s10533-016-0201-0&domain=pdf
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acquisition of lignin-shielded proteins in soils receiv-
ing N. However, N addition alone did not significantly
alter the quantity or quality of lignin monomers in any
treatment. Our results suggest that abiotic interactions
between N and phenolic compounds did not influence
lignin chemistry, but mineral N does alter microbial
enzyme and biomass dynamics, with potential longer-
term effects on soil C dynamics.
Keywords Maize � Extracellular enzymes � Lignin �Decomposition � Microbial community � Nitrogen
Introduction
Increases in mineral nitrogen (N) availability suppress
decay rates of highly lignified plant litter (Berg 2000;
Gallo et al. 2005; Wang et al. 2004). Soil mineral N is
known to decrease lignin-degrading enzyme activity,
especially in late stages of litter decomposition
(Freedman and Zak 2014; Gallo et al. 2004; Hobbie
et al. 2012; Waldrop and Zak 2006). Nitrogen
fertilization can also alter microbial community
composition and reduce microbial growth and respi-
ration (Fierer et al. 2012; Frey et al. 2014; Ramirez
et al. 2012). Although microbial responses to N
addition are well documented (reviewed in Burns et al.
2013), we still do not fully understand the abiotic
mechanisms that may inhibit lignin decomposition.
We lack a detailed study describing how chemical
reactions between N and lignin, independent from
microbial mechanisms, may contribute to the slowing
of lignin decay. With N deposition expected to alter
many aspects of carbon (C) cycling (Ochoa-Hueso
et al. 2013; Treseder 2008; Waldrop et al. 2004), we
need to understand how and why increased N avail-
ability inhibits the decay of cell wall phenolic
compounds to better predict how N deposition affects
organic matter turnover rates.
During organic matter decomposition, microorgan-
isms receive a low C ‘‘return on investment’’ from
lignin-degrading enzymes (Moorhead and Sinsabaugh
2006; Schimel and Weintraub 2003; Sugai and
Schimel 2003). Decomposers preferentially degrade
a fraction of water-soluble carbohydrates and other
labile soluble C before lignin in fresh litter, primarily
due to the higher C and nutrient returns (Berg 2000;
Rinkes et al. 2011). However, lignin degradability also
varies with its chemical composition. For example,
syringyl (S-) lignin subunits are more susceptible to
enzymatic oxidation than vanillyl (V-) type phenols
(Otto and Simpson 2006). Thus, both lignin quantity
and quality impact residue decomposition (Klotzbü-
cher et al. 2011; Machinet et al. 2011). Given that the
initial quality and quantity of lignin varies between
and within plant species (Amin et al. 2014), we need to
better understand how N availability influences the
biochemical mechanisms driving the degradation of
lignin (Grandy et al. 2008; Neff et al. 2002; Talbot
et al. 2012).
Because decomposers receive low C and energy
returns on lignin degradation, it is generally not used
as a sole C source (Kirk and Farrell 1987; Kirk et al.
1976). Lignin forms a resistant shield around cellulose
(i.e., lignocellulose) in plant cell walls (Amin et al.
2014; Dashtban et al. 2010). Decomposers may
increase their investment in lignin-degrading enzymes
to acquire C from shielded cellulose (Moorhead et al.
2013a; Rinkes et al. 2011). However, degrading high
concentrations of lignin may expend more energy than
is gained; yet, decomposers may still degrade lignin to
acquire N from shielded cell membrane proteins if no
other N is available (Craine et al. 2007). This
‘‘microbial N mining’’ hypothesis implies that decom-
posers may at times degrade lignin primarily to
acquire N. Thus, oxidative enzyme activities and
lignin decay can be suppressed by high soil N
concentrations (Carreiro et al. 2000; Keyser et al.
1976).
In addition to the effects of N on lignin degrading
enzymes, reactions between polyphenols and amino
compounds (i.e., ‘‘browning’’) can produce potentially
toxic compounds and recalcitrant aromatic groups that
could suppress lignin degradation (Fog 1988; Hodge
1953; Stevenson 1982). These same reactions between
lignin derived phenolics and N compounds may
decrease lignin-degrading enzyme efficiency and
further reduce the C return that decomposers get from
oxidative enzyme production (Schimel and Weintraub
2003; Tu et al. 2014). However, it is unclear if
browning is a common mechanism decreasing lignin
degradability.
The extent that browning may impact lignin
oxidation has been hypothesized to vary with soil pH
(Fog 1988). A possible explanation for the relationship
between the rate of browning reactions and soil pH is
an increased availability of N in neutral compared to
172 Biogeochemistry (2016) 128:171–186
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acidic pH soils (reviewed in Fog 1988; Soderstrom
et al. 1983). The influence of external factors such as
soil pH on browning may further exacerbate microbial
C limitation by increasing the energy required for
lignin degradation and/or decreasing the C return
(Treseder 2004). However, studies that explicitly
examine interactions between browning, soil pH, and
lignin chemistry are needed to disentangle the extrin-
sic and intrinsic factors underlying N inhibition of
lignin decay.
We selected maize internodes as the model system
in our study because of the wide variation in lignin
content between genotypes with similar tissue archi-
tecture. Our goal was to elucidate how interactions
between soil N availability, soil pH, and litter quality
alter (1) microbial lignolytic enzyme activities and (2)
lignin chemistry during maize decomposition. Thus,
we could determine how chemical reactions, indepen-
dent of microbial mechanisms, may contribute to the
slowing of lignin decay. To accomplish this goal, we
conducted a 478-day laboratory incubation using stem
internodes from three maize genotypes varying in
lignin quality and quantity mixed with either an acidic
or neutral pH soil, both with and without added
mineral N. We monitored microbial respiration and
biomass, lignin-degrading enzyme activity, litter
chemistry, and lignin monomer concentrations.
We tested two hypotheses aimed at disentangling
the microbial and chemical mechanisms underlying
why and how added N alters microbial dynamics and
lignin chemistry:
Hypothesis #1 Decomposer microorganisms
degrade lignin to acquire N, but if N is otherwise
available they stop producing lignolytic enzymes to
acquire N, thereby reducing lignin decay.
Hypothesis #2 Chemical reactions between lignin
and N make lignin more recalcitrant, which decreases
the ability of decomposers to break it down with
lignin-degrading enzymes.
We predicted that added N would decrease respi-
ration, microbial biomass, oxidative enzyme activi-
ties, and microbial acquisition of shielded
N-containing compounds in all treatments, with the
greatest inhibitory effect occurring in the most lignin
rich litter. We also predicted that chemical reactions
between N and lignin would have the largest effect on
total lignin monomer concentrations (i.e., syringyl
(S) ? vanillyl (V) ? cinnamyl (Cn) units) at a higher
soil pH.
Materials and methods
Maize genotypes
Three maize genotypes differing in lignin quality and
quantity (Table 1) were cultivated in experimental
fields at the INRA Lusignan experimental station (N
49�260, E 0�070, Vienne, France) and were harvested atphysiological maturity. The second internodes from
one normal line genotype (F2) and two brown midrib
Table 1 Chemicalcharacteristics of three
different genotypes of
maize internodes
Values represent the mean
(±SE) for each genotype
chemical category (n = 2).
Lowercase letters designate
significant differences
between genotypes for each
chemical characteristic
F2bm1Low lignin
F2Medium lignin
F292bm3High lignin
C to N ratio
Total C (% dry matter) 44.5 ± 0.12 a 44.1 ± 0.08 a 45.2 ± 0.01 a
Total N (% dry matter) 0.93 ± 0.03 a 0.98 ± 0.02 a 0.91 ± 0.02 a
C:N ratio (% dry matter) 47.8 ± 1.80 a 44.9 ± 0.06 a 49.2 ± 0.70 a
Labile content
Soluble (% dry matter) 39.2 ± 2.2 a 44.8 ± 1.8 a 25.7 ± 1.2 b
Total sugars (% dry matter) 45.0 ± 1.6 a 44.0 ± 0.2 a 44.3 ± 0.3 a
Lignin/structural fraction
Cell wall (% dry matter) 60.3 ± 2.2 b 55.2 ± 1.8 b 74.3 ± 1.2 a
Klason lignin (% cell wall) 10.4 ± 0.2 c 15.0 ± 0.6 a 13.0 ± 0.4 b
Klason lignin (% dry matter) 6.3 ± 0.1 c 8.3 ± 0.3 b 9.7 ± 0.3 a
S/V ratio 0.86 ± 0.03 a 0.81 ± 0.02 a 0.31 ± 0.02 b
Biogeochemistry (2016) 128:171–186 173
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mutants (F2bm1 and F292bm3) were used in the
incubation. The total C and N content of each
genotype was determined by elemental analysis (NA
1500, Fisons Instruments) and the soluble and cell wall
content was determined by neutral detergent fiber
(NDF) extraction following the method described by
Goering and Van Soest (1970). In brief, the soluble
fraction was removed by boiling 1 g of maize
internodes in deionized water at 100 �C for 60 min.The remaining NDF fraction corresponded to the cell
walls. Total sugar content of the residue (i.e., soluble
and cell wall fraction) was determined by the method
described by Blakeney et al. (1983) using a two-step
sulfuric acid hydrolysis. Lignin content of the residue
was approximated as the acid-unhydrolyzable residue
remaining after sulfuric acid hydrolysis according to
the Klason lignin (KL) determination (Monties 1984).
Results of these analyses are found in Table 1. Based
primarily on initial lignin quantity (% dry matter) and
quality (S/V ratio), we refer to the three maize
genotypes as follows: (1) F2bm1 = Low lignin geno-
type, (2) F2 = Medium lignin genotype, (3) F292-bm3 = High lignin genotype. These designations are
based on the higher initial lignin content of F2 and
F292bm3 than F2bm1 and lower S/V ratio and soluble
content in F292bm3 compared to other genotypes
(Table 1).
Soil collection
Two Typic Udipsamment soils varying in pH but
similar in many soil properties (Table 2) were col-
lected in September of 2009. The acidic pH soil
(4.9 ± 0.2) was collected from the Kitty Todd Nature
Preserve (N 41�370, W 83�470) and the neutral pH soil(6.7 ± 0.3) from the Oak Openings Preserve Metro-
park (N 41�330, W 83�500), which are approximately11 km apart and located in Northwest Ohio. These
sandy sites were selected due to their low C (\1 %)and nutrient concentrations. Soil cores were collected
from the top 5 cm (the depth with the highest
biological activity) from a 10 m2 area at both sites,
sieved (2 mm mesh) to remove as much coarse debris
and organic matter as possible, thoroughly mixed, and
pre-incubated for 3 months in a dark 20 �C incubatorat 45 % water-holding capacity (WHC). This is the
WHC that maximizes respiration in both soils (Rinkes
et al. 2013, 2014). The pre-incubation allowed for
microorganisms to acclimate to experimental
conditions and to metabolize as much extant labile C
as possible.
Incubation experiment
A long-term (478-day) laboratory incubation was
established in 473 ml wide mouth canning jars to
monitor lignin decay, which predominately occurs in
late stages of decomposition. One hundred-twenty
litter and soil treatments (3 litter types 9 2
soils 9 2 N addition levels 9 10 harvests) and forty
soil-only control treatments (2 soil types 9 2 N
addition levels 9 10 harvests) were replicated four
times, and incubated together in a random arrange-
ment. Litter treatment jars contained 50 g dry soil
adjusted to 45 % WHC mixed with dry maize stem
internode fragments (0.5 cm length/1–1.5 cm diame-
ter) at a rate of 3000 mg C kg-1 soil. Soil-only control
jars contained 50 g dry soil adjusted to 45 % WHC.
Nitrogen (ammonium nitrate, 70 mg N kg-1 soil) was
added to half of the treatment and soil-only control jars
as an initial pulse at the beginning of the experiment
(Recous et al. 1995). The control groups received an
equivalent amount of water, but did not receive
supplemental N addition. Respiration was monitored
frequently (see below) and destructive harvests
occurred on days 0 (*8 h), 27, 58, 84, 120, 172,238, 316, 390, and 478. Each destructive harvest
included enzyme assays, determination of microbial
biomass-C, and dissolved organic C (DOC).
Table 2 General soil properties averaged (± SE) for theUdipsamment soils used in the 478-day incubation (n = 4)
Soil properties Acidic Neutral
pH 4.9 ± 0.2 b 6.7 ± 0.3 a
% C 0.7 ± 0.07 a 0.6 ± 0.03 a
% N 0.06 ± 0.01 a 0.05 ± 0.01 a
C/N ratio 12.1 ± 0.62 a 12.7 ± 0.87 a
Microbial biomass 27.2 ± 4.3 b 43.8 ± 1.6 a
Ammonium 1.3 ± 1.1 a 0.2 ± 0.1 a
Nitrate 1.8 ± 0.1 a 0.76 ± 0.05 b
Units are lg-C g soil-1 for microbial biomass and lg-N gsoil-1 for inorganic nutrient concentrations. Lowercase letters
designate significant differences between soils for each
property
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C mineralization
The amount of C mineralized after 7, 11, 18, 31, 53,
89, 123, 159, 219, 306, and 478 days was measured in
litter addition treatment groups, soil-only controls, and
four sample-free jars (blanks). Sodium hydroxide
(NaOH) traps captured CO2 produced during decom-
position. The amount of NaOH in each trap was
optimized based on the anticipated respiration rate in
each stage of decay (i.e., 10 ml of 2 M NaOH on day
18 but only 8 ml on day 306). Traps were changed less
frequently as respiration rates decreased and became
less dynamic over time. Traps were analyzed using the
BaCl2/HCl titration method (Snyder and Trofymow
1984). In brief, 2 ml of BaCl2 were added to the
NaOH to precipitate the trapped CO2 as BaCO3,
followed by 5 drops of thymophthalein pH indicator.
The carbonic acid trapped in the NaOH was then back
titrated with 0.1 N HCl. The calculation of C trapped
required subtracting the equivalents of acid used in
titrating a sample from the equivalents used to titrate
traps in the sample-free blanks. Jar headspace CO2concentrations were also measured with a Li-820
infra-red gas analyzer (LI-COR Biosciences, Lincoln,
Nebraska, USA) during early decay. This method was
used to calculate cumulative C mineralization during
the dynamic first week of decomposition, as NaOH
traps were saturated with CO2 and the titration values
could not be used.
Lignolytic enzyme assays
Colorimetric assays were conducted in 96-well
microplates for phenol oxidase (Phenox), which is a
lignin-degrading enzyme, using 2,20-azino-bis-3-ethylbenzothiozoline-6-sulfononic acid (ABTS) as a
substrate (Floch et al. 2007; Saiya-Cork et al. 2002).
ABTS was previously found to be a more reliable
substrate than L-3,4-dihydroxyphenylalanine (L-
DOPA) in this maize litter (reported in German et al.
2011). Sample slurries were prepared by homogeniz-
ing 100–400 mg of wet internodes with 50 ml of
50 mM sodium acetate buffer (pH 5). The internode
and buffer mixture was homogenized for 1 min using
a Biospec Tissue Tearer (BioSpec Products, Bartles-
ville, OK). Assay wells included 200 ll aliquots ofslurry followed by the addition of 100 ll of 1 mMABTS. Negative controls received 200 ll of bufferand 100 ll ABTS and blank wells received 200 ll of
slurry and 100 ll of buffer. Plates were incubated forat least 2 h at 20 �C in darkness and a Bio-TekSynergy HT Plate Reader (Bio-Tek Inc., Winooski,
VT, USA) was used to measure absorbance at 420 nm
(German et al. 2011).
After correcting for negative controls and blank
wells, enzyme activity rates were expressed as
lmol h-1 g dry litter-1. Cumulative enzyme activitywas calculated by integrating enzyme activity over
time and expressed in units of mmol of substrate
oxidized per g of litter (mmol g-1).
Microbial biomass
Maize internodes (removed from each litter ? soil
treatment and brushed free of soil particles with a
2 mm paint brush) and 3 sample-free blanks were
extracted for DOC by adding 8 ml of 0.5 M potassium
sulfate and agitating on an orbital shaker for 1 h.
Samples were vacuum filtered through Pall A/E glass
fiber filters and frozen at -20 �C until analyses wereconducted. Microbial biomass carbon (MB-C) was
quantified using the modification of the chloroform
fumigation-extraction method (Brookes et al. 1985)
described by Scott-Denton et al. (2006). 100–400 mg
(wet weight) of internodes were combined with 0.5 ml
of ethanol free chloroform, followed by incubation for
24 h. Flasks were then vented, extracted as described
above, and analyzed for DOC on a Shimadzu TOC-
VCPN analyzer (Shimadzu Scientific Instruments Inc.,
Columbia, MD, USA). No correction factor for
extraction efficiency (kEC) was applied, as it is
unknown for these samples. It was assumed that
extraction efficiency was constant among samples.
Litter chemical composition
We analyzed the chemical composition of the maize
medium lignin genotype with pyrolysis–gas chro-
matography and mass spectrometry (py-GCMS) after
decomposing for 0, 120, and 478 days. This genotype
was selected because it contained both a high initial
labile and lignin content (% cell wall). We also found
some of the strongest contrasts between N? and N-
treatments for C mineralization, microbial biomass,
and lignin-degrading enzyme activities in the medium
lignin litter. Samples were pyrolysed at 600 �C for20 s on a CDS Pyroprobe 5150 pyrolyzer (CDS
Analytical, Inc., Oxford, PA, USA). Samples were
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then transferred to a Thermo Trace GC Ultra gas
chromatograph (Thermo Fisher Scientific, Austin, TX,
USA) where they were separated on a 60 m fused
silica capillary column over the course of approxi-
mately 60 min with a starting temperature of 40 �Cand final temperature of 310 �C. Compounds werethen ionized via ion trap on a Polaris Q mass
spectrometer (Thermo Fisher Scientific). The Auto-
matedMass Spectral Deconvolution and Identification
System (AMDIS, V 2.65) and the National Institute of
Standards and Technology (NIST) compound library
were used to analyze peaks. Compound abundances
(i.e., lignin, lipid, N bearing, phenol, polysaccharide,
protein, unknown) are reported as the proportion of
total sample composition and were determined rela-
tive to the total ion signal from all identified peaks.We
compared individual compound abundance from both
phenol and N-bearing classes on days 120 and 478 to
identify any novel chemical compounds occurring
after N addition.
Lignin chemistry
Litter treatments (internodes ? soil) were oxidized
with cupric oxide (CuO) after 0, 120, and 478 days
following the procedure of Hedges and Ertel (1982)
and adapted fromKogel (1986). One g of CuO, 100 mg
ammonium iron (II) sulfate hexahydrate and 15 ml of
2 M NaOH purged with N gas were added to Teflon-
line bombs containing samples. After heating for 2 h at
170 �C, the bombs were cooled at room temperatureandmethanolwater (1:1, v/v) solutions of ethylvanillin
and 3,4,5-trimethoxy-trans-cinnamic acid were added
to the reaction mixture as internal standards. The
reaction mixture was acidified to pH 1–2 using 6 M
HCl and centrifuged (10 min at 10,000 rpm). The
residues were washed with 10 ml of deionized water
prior to centrifugation. The combined supernatants
were extracted three times with 25 ml of dichloro-
methane. Anhydrous Na2SO4 was added to the com-
bined organic phases to remove any remaining water.
The dichloromethane extract was evaporated at 40 �Cunder reduced pressure. The monomers recovered by
CuO oxidation were determined by HPLC (Waters,
2690). The dried extracts were dissolved in 1 ml
methanol:water (1:1, v/v) and filtered (0.45 lm) priorto injection onto a Spherisorb S5ODS2 (Waters, RP-
18, 250 9 2.6 mm) column. The lignin oxidation
products were detected using a photodiode array UV
detector (Waters, 996). The vanillyl (V) and syringyl
(S) units were quantified at 280 nm using the ethyl-
vanillin as an internal standard while cinnamyl (Cn)
units were quantified at 302 nm using 3, 4, 5
trimethoxy-trans-cinnamic acid (Chen 1992). All
monomers were quantified using appropriate reference
standards. The concentration of V-type monomers was
calculated as the sum of the concentrations of vanillin,
acetovanillone, and vanillic acid. The concentration of
S-type monomers was calculated as the sum of the
concentrations of syringic acid, syringaldehyde, and
acetosyringone. The concentration of Cn-type mono-
mers was calculated as the sum of the concentrations of
ferulic and p-coumaric acids (Hedges and Ertel 1982).
The sum of V, S, and Cn type phenols released from
lignin macromolecules was used to approximate the
total amount of lignin phenols (Bahri et al. 2006; Kogel
1986). For all samples, the mean values were obtained
from two replicate CuO oxidations.
Data analysis
Differences in the initial characteristics of the three
maize genotypes were analyzed by analysis of vari-
ance (ANOVA). Cumulative C mineralization and
cumulative Phenox activity were analyzed using
separate three-way ANOVA’s with maize genotype,
soil pH, and N addition (? or-) and their interactions
as factors. Enzyme efficiency (C released per unit
enzyme activity) was determined from the slope of the
regression of cumulative C mineralization (mg litter C
respired) and cumulative enzyme activities (lmol gdry litter-1) over all harvest dates (Amin et al. 2014;
Sinsabaugh et al. 2002). Carbon mineralization and
enzyme activities measurements were not always
taken on the same date. Thus, cumulative C mineral-
ization values were adjusted to represent the projected
cumulative amount of litter C respired on each enzyme
measured date. Microbial biomass-C was analyzed on
days 0, 120, and 478 using separate three-way
ANOVA’s with maize genotype, soil pH, and N
addition and their interactions as factors. The relative
abundances of lignin, lipids, N bearing compounds,
phenols, polysaccharides, and proteins in the medium
lignin genotype maize litter were analyzed on days
120 and 478 using a two-way MANOVA with soil pH
and N addition and their interaction as factors. Cn/V
ratios, S/V ratios, and the sum of V ? S ? Cn
monomers were analyzed on days 120 and 478 using
176 Biogeochemistry (2016) 128:171–186
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a three-way MANOVA with maize genotype, soil pH,
and N addition and their interactions as factors.
Differences among groups were considered signif-
icant if P B 0.05 and were compared using Tukey
multiple comparison post hoc tests. Data were ana-
lyzed using SPSS Statistics version 21.0.
Results
C mineralization
After 478 days, C mineralized ranged between 39.4
and 53.6 % of added C (Fig. 1). Nitrogen addition
increased the amount of litter C remaining at the end of
the experiment across all treatments (P\ 0.01;F = 14.96). Nitrogen had the weakest effect on the
high lignin genotype in the neutral pH soil (Fig. 1F).
On average, 5 % more of the initial litter C added was
respired in neutral than acidic treatments, which
resulted in a significant pH effect on C mineralization
(P\ 0.01; F = 13.59; Supplementary Table 1). Thegenotype effect on C mineralization was quite low
(Supplementary Table 1).
Lignin degrading enzyme activity
Nitrogen addition significantly decreased cumula-
tive lignin degrading enzyme (i.e., Phenox) activity
compared to ambient conditions (Fig. 2; Supple-
mentary Table 1) and suppressed cumulative activ-
ity by more than 50 % in the low pH, high lignin
treatment (Fig. 2C). This resulted in a significant
N 9 genotype interaction effect (P = 0.04;
F = 3.47). In addition, cumulative Phenox activity
was greater in the acidic than neutral pH treatments
(P\ 0.01; F = 7.83). Cumulative Phenox activityin the low lignin litter was lower than in the
medium and high lignin genotypes (P\ 0.01;F = 33.17).
Enzyme efficiencies calculated from the slope
(higher slope = higher enzyme efficiency) of the
relationship between cumulative respiration and
cumulative phenol oxidase activity were consistently
lower in the N- than N? treatments for all genotypes
(Table 3). Additionally, slope values were lower for
the higher lignin litter types than the low lignin litter
(Table 3). All relationships were positive and highly
significant (P\ 0.01).
Fig. 1 Cumulative litter Cmineralization (mg C kg
soil-1) over a 478-day
laboratory incubation for the
low (A, B), medium (C,D) and high (E, F) ligninmaize genotypes mixed with
either an acidic or neutral
pH soil, both with and
without added N. Error bars
show the standard error of
the mean (n = 4). Asterisks
denote significant
differences (P\ 0.05)between N treatments for
each genotype and pH
combination on day 478.
The total amount of litter C
mineralized is designated as
a percentage (%)
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Microbial biomass dynamics
MB-C changed significantly over time when day was
included as a factor in the ANOVA (P\ 0.01;F = 14.49). On day 0, there was a significant genotype
(P = 0.04; F = 3.55) effect on MB-C (Supplemen-
tary Table 2). Post-hoc tests revealed MB-C was
higher in the low and medium lignin than high lignin
genotype. There was a significant pH effect on MB-C
on day 120 (P\ 0.01; F = 13.17), as MB-C washigher in the neutral than acidic pH treatments
(Fig. 3). On day 478, there was a significant N 9 pH
effect (P\ 0.01; F = 8.88), primarily due to lowerMB-C in the N amended, low pH treatments compared
to ambient conditions (Fig. 3). Overall, there were
significant N (P\ 0.01; F = 7.18) and pH effects(P\ 0.01; F = 13.45) on MB-C after day 0. This wasprimarily due to lower MB-C in the N? than N-
treatments in the acidic pH soils (Supplementary
Fig. 1).
Changes in litter chemical composition
There were no significant N or pH effects on the
relative abundance of lignin derivatives or polysac-
charide and non-protein N bearing compounds for
the medium lignin genotype over days 120 and
478 (Fig. 4A–C; Supplementary Table 3). The
lignin:polysaccharide ratio was[1 in the N? treat-ments, but\1 under ambient conditions for litter fromboth soils when averaged over days 120 and 478
Fig. 2 Cumulative phenol oxidase activities (mmol g litter-1)over a 478-day laboratory incubation for the A low, B medium,and C high lignin maize genotypes mixed with either an acidicor neutral pH soil, both with and without added N. Error bars
show the standard error of the mean (n = 4). Lowercase letters
represent significant differences between treatments for each
genotype on day 478
Table 3 Enzyme efficiency (C released per unit enzyme activity) was determined from the slope (R2) of the regression of cumu-lative C mineralization (mg litter C respired) and cumulative phenol oxidase activity (lmol g dry litter-1) over all harvest dates
Litter treatment N? Treatment
Slope of regression (R2)
N- Treatment
Slope of regression (R2)
Low lignin (F2bm1)
pH 4.9 0.0053 (0.96) 0.0038 (0.98)
pH 6.7 0.0046 (0.91) 0.0042 (0.96)
Medium lignin (F2)
pH 4.9 0.0018 (0.99) 0.0011 (0.92)
pH 6.7 0.0025 (0.96) 0.0016 (0.94)
High lignin (F292bm3)
pH 4.9 0.0024 (0.92) 0.0012 (0.98)
pH 6.7 0.0026 (0.93) 0.0018 (0.95)
Higher enzymatic efficiency is associated with higher slope values. All relationships were positive and highly significant (P\ 0.01)
178 Biogeochemistry (2016) 128:171–186
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(n = 8 per soil). Thirteen novel N-bearing compounds
(i.e., found in the N? , but not N- treatments) were
identified on days 120 and 478. However, each
compound comprised\0.8 % of the total compoundabundance (Supplementary Table 4).
Protein abundance was significantly higher in the
N- than N? treatments and greater in litter mixed
with the neutral than acidic soil (Fig. 4D). This
resulted in significant N (P\ 0.01; F = 10.37) andpH (P\ 0.01; F = 12.67) effects on protein abun-dance and a relatively high but statistically insignif-
icant interaction effect (P\ 0.06; F = 4.09).Lipids were significantly higher in the N- than
N? treatment in the neutral pH soil on day 478
(Fig. 4E). This resulted in a significant N 9 pH effect
on lipid abundance (P = 0.05; F = 4.91). Phenol
abundance was greater in acidic than neutral soil
(P = 0.05; F = 4.17; Fig. 4F).
Lignin chemistry
There were no significant N or pH effects on the S/V
ratio (S lignin subunits more susceptible to enzymatic
oxidation than V phenols). There was a significant
genotype effect (P\ 0.01; F = 25.67), primarily dueto lower S/V ratios in the high lignin litter than in the
low and medium lignin genotypes (Fig. 5). Initial
(Day 0) S/V ratios ranged from 0.75 to 0.81 (low
lignin), 0.89–0.93 (medium lignin), and 0.70–0.98
(high lignin).
There was no significant N effects on the Cn/V ratio
over days 120 and 478 (Supplementary Table 5). Cn/
V ratios were higher in the acidic soil compared to
neutral pH treatments, which resulted in a significant
pH effect (P\ 0.01; F = 17.36). There was a signif-icant genotype effect (P\ 0.01; F = 5.99), primarilydue to lower Cn/V ratios in the low lignin litter than in
Fig. 3 Microbial biomass-C (MB-C) for all genotypes in bothsoil types (acidic and neutral pH) with and without added N.
Values represent the mean ± SE for each treatment on day 0
(n = 4), day 120 (n = 4), and day 478 (n = 4). Units are mg C
g dry litter-1. There was a significant genotype (low and
medium lignin[ high lignin treatment) effect on day 0. There
was a significant pH effect (neutral[ acidic) on day 120 (notethe differences in scale between pH 4.9 and pH 6.7 figures).
There was a significant N 9 genotype interaction on day 478.
Asterisks denote significantly higher (P\ 0.05) MB-C in N-compared to N? treatments for each genotype 9 pH combina-
tion on a harvest date
Biogeochemistry (2016) 128:171–186 179
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the high lignin genotype (Supplementary Fig. 2).
Initial (Day 0) Cn/V ratios ranged from 0.10 to 0.20
(low lignin), 0.09–0.12 (medium lignin), and
0.09–0.22 (high lignin).
There were no significant N effects on the total
amount of lignin monomers (i.e., V ? S ? Cn) over
days 120 and 478 (Supplementary Table 5). There was
a significant genotype effect (P = 0.02; F = 4.47) on
the total amount of lignin monomers over days 120
and 478, primarily due to higher monomer concentra-
tions in the medium lignin litter than low and high
lignin genotypes (Fig. 6). Total lignin monomers
ranged from 96 to 135 (low lignin), 143–178 (medium
lignin), and 137–225 (high lignin) lmol g Org C-1 onDay 0.
Discussion
N, pH, and litter chemistry effects on lignin
derivatives
We hypothesized that abiotic reactions between lignin
and N make lignin more recalcitrant to microbial
degradation. Despite a trend toward higher lignin
monomer quantity in most N addition treatments, the
total abundance of lignin monomers (quantity) and
S/V ratios (quality) did not differ significantly
between N addition and ambient treatments for any
genotype over the 478-day incubation. Similarly, N
had little effect on lignin derivatives and phenol
abundance determined using py-GCMS in our med-
ium lignin neutral pH soil treatments, contradicting
the Fog (1988) hypothesis that browning reactions
especially increase lignin recalcitrance in higher pH
soils. Indeed, a relatively higher concentration of
lignin monomers would have been expected in our N
addition treatments compared to controls if added N
decreased the degradability of lignin. We did identify
some novel compounds (i.e., found in N? but not N-
treatments) following N enrichment in our medium
lignin litter, but their abundances were very low
overall (\1 % of total compound abundance). Thissuggests that interactions between N and lignin
derivatives did not significantly increase the produc-
tion of more recalcitrant compounds that inhibited
lignin degradation. Furthermore, the weakest effect of
mineral N on C mineralization occurred in the highest
lignin genotype (Fig. 1), indicating that elevated N did
not increase lignin recalcitrance. Nitrogen addition
also increased enzyme efficiency compared to ambient
conditions in all of our treatments for every genotype.
Fig. 4 Relative abundanceof A polysaccharides,B lignin derivatives, C Nbearing compounds,
D proteins, E lipids, andF phenolic compounds inmaize before decomposition
(dashed lines) and after 120
and 478 days of
decomposition in acidic and
neutral soil treatments with
and without added N. Error
bars show the standard error
of the mean (n = 4).
Significant differences
(P\ 0.05) are noted withina panel as either nitrogen
(N) or pH (pH) effects, and
significant interactions
between the two (N 9 pH)
180 Biogeochemistry (2016) 128:171–186
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Thus, our findings suggest that chemical reactions
between by-products of lignin degradation and N did
not significantly increase lignin recalcitrance or limit
the ability of decomposers to break down phenolic
compounds.
No study we are aware of has directly tested the Fog
(1988) hypothesis by examining the combined effects
of N, soil pH, and litter chemistry on lignin decay.
Thomas et al. (2012) found that chronic N addition had
little effect on the biochemical composition of lignin-
derived molecules in a sugar maple forest stand. Gallo
et al. (2005) concluded that reactions directly incor-
porating N into soil organic matter (SOM) were not a
major mechanism influencing ecosystem responses to
mineral N addition. In comparison, our study focused
explicitly on the Fog (1988) hypothesis and found
weak effects of N on lignin chemistry across contrast-
ing chemistries of maize litter, and across soils varying
in pH. Thus, ‘‘browning’’ was not an important
chemical mechanism driving N inhibition of lignin
decay in our maize litter. Overall, our results do not
support the hypothesis that chemical reactions
between N and lignin make lignin more resistant to
decomposition.
In contrast to the effects of mineral N, we found that
genotype had variable effects on the quantity and
quality of maize lignin monomers. The sum of phenyl
propane units (i.e., V ? S ? Cn) is commonly used to
measure lignin concentrations, even if extraction yield
may be low (Klotzbücher et al. 2011; Machinet et al.
2011), while decreases in S/V ratios over time
represent a gradual decline in lignin quality (Otto
and Simpson 2006). We found that the S/V propor-
tions tended to remain constant in the low lignin
genotype treatments over the first 120 days of incu-
bation. This suggests that minimal lignin degradation
occurred as labile constituents were preferentially
degraded (Bertrand et al. 2006; Machinet et al. 2009).
Typically, labile substrates are efficiently used by
Fig. 5 S/V ratio on days 120 and 478 during a laboratoryincubation of low (A), medium (B), and high (C) lignin maizegenotypes. Each genotype was mixed with either an acidic or
neutral pH sandy soil, both with and without added N. Nitrogen
addition had no significant effect on S/V ratios
Fig. 6 Total lignin monomer concentrations (S ? V ? Cnunits) on days 120 and 478 during a laboratory incubation of
low (A), medium (B), and high (C) lignin maize genotypes.Each genotype was mixed with either a low or neutral pH sandy
soil, both with and without added N. Added N had no significant
effect on total monomer abundance
Biogeochemistry (2016) 128:171–186 181
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decomposers during early stages of decay (Moorhead
et al. 2013b; Rinkes et al. 2013, 2014) and may be the
dominant source of microbial products contributing to
stable SOM (Cotrufo et al. 2013; Grandy and Neff
2008; Six et al. 2006; Stewart et al. 2015). Given the
ratio of more degradable S- to more recalcitrant
V-units (Kogel 1986; Otto and Simpson 2006) did not
significantly change, our results indicate that the most
labile litter became relatively enriched in lignin
throughout the incubation.
V ? S ? Cn yields and S/V ratios were lower on
day 478 compared to day 0 in the high lignin bm3genotype. This mutant is often characterized by low
concentrations of labile ether-linked syringyl units
(Barriere et al. 2004; Machinet et al. 2011). In
addition, Cn/V ratios generally decreased in this litter
over the incubation. We also found higher cumulative
potential Phenox activity in the high lignin than low
lignin genotype. This suggests lignin shielded cellu-
lose or other labile C compounds were possibly more
important resources to decomposers earlier in decay in
the highest lignin litter. Thus, microorganisms may
degrade lignin to obtain shielded C sources when
necessary, especially in litter types with a high amount
of lignin and low soluble C content.
N, pH, and litter chemistry effects on microbial
function
We hypothesized that under N enrichment, lignin
degradation would decrease due to lower microbial N
demand (Moorhead and Sinsabaugh 2006). Indeed, N
addition decreased oxidative enzyme activities across
all treatments (Fig. 2). This ubiquitous decline sug-
gests that decomposers may have used labile C
substrates in maize litter to provide the energy to
‘‘mine’’ lignin and obtain N shielded by the cell wall
phenolic fraction (Chen et al. 2013; Talbot et al. 2012).
Because the acid insoluble fraction of litter does not
provide sufficient C and energy yields upon degrada-
tion, decomposers may decrease production of ener-
getically costly lignin-degrading enzymes if the
availability of mineral N increases (Craine et al.
2007; Kirk and Farrell 1987). In contrast to enzyme
activities, we found an overall increase in lignin-
degrading enzyme efficiency in our N? treatments
compared to ambient conditions. It is possible that N
stimulated the breakdown of more labile C compounds
than lignin, which increased the amount of C released
per unit enzyme activity in our N? treatments.
Nitrogen addition also resulted in greater retention of
total lignin derivatives relative to polysaccharides in
the medium lignin litter incubated in both soils.
Previous studies suggest that declines in oxidative
enzyme activity are often linked with increases in
lignin-derived C under elevated N levels (Grandy et al.
2008; Saiya-Cork et al. 2002). It is possible that the
higher lignin:polysaccharide ratio reflects lower
biomass accumulation resulting in decreased micro-
bial polysaccharides in N addition treatments, espe-
cially in our acidic soil. These findings suggest that
microorganisms may degrade lignin more often under
N limiting conditions, possibly to obtain shielded N
compounds (Craine et al. 2007; Moorhead and Sins-
abaugh 2006). However, a reduction in fungal abun-
dance following N addition could also result in
significant decreases in oxidative enzyme activities
(Treseder 2004).
It is possible that greater microbial N demand due
to higher microbial biomass without added N stimu-
lated oxidative enzyme production to obtain proteins
shielded by lignin. We found that microbial biomass
and protein abundance were often lower in the
N? than N- treatments in our medium lignin maize
litter, especially in our neutral pH soil on day 120
(Figs. 3, 4). Because microorganisms are a dominant
source of proteins during decomposition (Schulze
2004), it is likely that the suppressive effect of N
addition on microbial biomass reduced overall protein
abundance (Ramirez et al. 2012). We speculate that
low microbial biomass and fungal activity in our
N? treatments decreased overall protein abundance
and reduced microbial demand for lignin-shielded
proteins in our medium lignin litter (Frey et al. 2004;
Treseder 2008).
N, pH, and litter chemistry effects on microbial
respiration and biomass dynamics
Nitrogen availability, soil pH, and litter chemistry
influence microbial dynamics, but their effects are
dependent on the stage of decay. Rapid increases in
microbial biomass occurred in our low and medium
lignin genotypes immediately following litter addition
(within 8 h), with the highest concentrations in the
neutral pH soil (Fig. 3). In addition, microbial respi-
ration rates were elevated (Fig. 1), but lignin-degrad-
ing enzyme activities were low (Fig. 2) during the first
182 Biogeochemistry (2016) 128:171–186
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few days of incubation for these litters. This suggests
that fast-growing microorganisms preferentially
degraded water-soluble compounds and labile poly-
meric C substrates during initial decay (Glanville et al.
2012; Rinkes et al. 2014). Machinet et al. (2009) found
that early colonizing microorganisms were influenced
by the chemical quality of maize roots, as they
colonized genotypes with a high cell wall sugar
content more rapidly than those with high lignin
content. Similarly, we found the lowest microbial
biomass and activity in the highest lignin genotype
during this early colonization phase. We also found
that microbial biomass during the initial harvest was
more than 70 % lower in the acidic than neutral pH
soils across all low and medium lignin genotype
treatments. We speculate that the pH response in these
litters was due to higher bacterial activity and growth
in the neutral pH soil. Bacterial abundance is posi-
tively correlated with soil pH and frequently doubles
between pH 4 and 8 (Rousk et al. 2009, 2010). It is
likely that the neutral pH soil accelerated bacterial
colonization and assimilation of abundant water-
soluble substrates in the lower lignin genotypes.
However, it is also possible that differences in initial
microbial community composition influenced these
dynamics. Overall, our findings suggest that litter
chemistry and soil pH influence how quickly decom-
posers colonize fresh litter.
Nitrogen addition and soil pH were strong
controls on microbial activity, growth, and possibly
community composition during later decay stages.
Nitrogen fertilization decreased the total amount of
C mineralized across all of our maize treatments
(Fig. 1) and reduced microbial biomass by approx-
imately 50 % after day 0 in our acidic pH
treatments (Supplementary Fig. 1). During this
same time period, N addition only reduced micro-
bial biomass by an average of 8 % across all
neutral pH soil treatments, which generally had the
highest amounts of C mineralized. It is not
uncommon for N fertilization to consistently reduce
microbial respiration (Ramirez et al. 2010) or to
suppress microbial biomass by as much as 20–35 %
across a wide range of soil types (Ramirez et al.
2012; Treseder 2008 and references therein). White-
rot fungi and other saprophytic fungi often respond
negatively to N addition, especially in microcosms
(Entry 2000; Fog 1988), while saprophytic bacteria
are favored by N amendments (Freedman and Zak
2014). Thus, chronic N amendments tend to
decrease fungal: bacterial ratios and reduce fungal
degradation of lignin (Bowden et al. 2004; Frey
et al. 2004; Treseder 2008; Wallenstein et al.
2006). Given that fungi tend to be more acid
tolerant than bacteria, it is possible that fungi were
a more active and dominant component of our
lower pH soils (Joergensen and Wichern 2008;
Strickland and Rousk 2010). We speculate that the
inhibitory effect of N on microbial community
composition and activity (i.e., likely fungi) had a
greater influence in our acidic soil, which may have
driven the strong contrasts in microbial dynamics
between soil types.
Conclusions
N fertilization has the potential to significantly
impact C cycling rates, and is likely to influence
biogeochemical responses to elevated CO2 and
climate change. We provide data describing the
microbial and chemical mechanisms that give rise
to the inhibitory effect of N on lignin decay. This
study shows that N addition suppresses C mineral-
ization, microbial biomass, and lignolytic enzyme
activity, but does not alter lignin chemistry during
decomposition of maize. We provide some of the
first evaluations of the Fog (1988) hypothesis,
which suggests that chemical reactions between N
and lignin make lignin more resistant to decompo-
sition. Our results do not support this hypothesis, as
N addition did not alter the quality or quantity of
lignin monomers, even in our highly lignified maize
genotypes and neutral pH soil. Given the ubiquitous
decline in lignin-degrading enzyme activities fol-
lowing N addition, it is possible that decomposers
may degrade lignin to obtain N. Elevated lignin-
degrading enzyme activity in our high lignin
genotype suggests that decomposers may also break
down lignin to acquire C in the absence of high
energy labile C compounds.
Acknowledgments This research was supported by an NSFEcosystems Program Grant (# 0918718) to MNW and ASG and
the NSF Research Coordination Network on Enzymes in the
Environment Grant (# 0840869). For field and laboratory
assistance, we thank Bethany Chidester, Dashanne Czegledy,
Michael Elk, Mallory Ladd, Ryan Monnin, Steve Solomon,
Heather Thoman, Logan Thornsberry, Eric Wellman, Travis
Biogeochemistry (2016) 128:171–186 183
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White, and Megan Wenzel. We also thank three anonymous
reviewers whose suggestions greatly improved this work.
Author contributions MNW and IB conceived the project.Microbial analyses were conducted by ZLR. CuO analyses were
performed by BZA and IB. ASG and KW provided the py-
GCMS data. ZLR and BZA analyzed the data. ZLR wrote the
article with input from the other authors.
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Nitrogen alters microbial enzyme dynamics but not lignin chemistry during maize decompositionAbstractIntroductionMaterials and methodsMaize genotypesSoil collectionIncubation experimentC mineralizationLignolytic enzyme assaysMicrobial biomassLitter chemical compositionLignin chemistryData analysis
ResultsC mineralizationLignin degrading enzyme activityMicrobial biomass dynamicsChanges in litter chemical compositionLignin chemistry
DiscussionN, pH, and litter chemistry effects on lignin derivativesN, pH, and litter chemistry effects on microbial functionN, pH, and litter chemistry effects on microbial respiration and biomass dynamics
ConclusionsAcknowledgmentsReferences