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 (medium

lignin)\ F2bm1 (low lignin)). Maize stem internodes

of 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. Weintraub

Department of Environmental Sciences, University of

Toledo, Toledo, OH 43606, USA

e-mail: zachary.rinkes@rockets.utoledo.edu

I. Bertrand � B. A. Z. Amin

INRA, 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

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 (Klotzbu-

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

123

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 Chemical

characteristics 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

F2bm1

Low lignin

F2Medium lignin

F292bm3

High 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

123

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 approximately

11 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 incubator

at 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 the

Udipsamment 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 g

soil-1 for inorganic nutrient concentrations. Lowercase letters

designate significant differences between soils for each

property

174 Biogeochemistry (2016) 128:171–186

123

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 CO2

concentrations 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 of

slurry followed by the addition of 100 ll of 1 mM

ABTS. Negative controls received 200 ll of buffer

and 100 ll ABTS and blank wells received 200 ll of

slurry and 100 ll of buffer. Plates were incubated for

at least 2 h at 20 �C in darkness and a Bio-Tek

Synergy 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 activity

was 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 were

conducted. 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 for

20 s on a CDS Pyroprobe 5150 pyrolyzer (CDS

Analytical, Inc., Oxford, PA, USA). Samples were

Biogeochemistry (2016) 128:171–186 175

123

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 were

then 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 temperature

andmethanolwater (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) prior

to 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 g

dry 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

123

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). The

genotype 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 activity

in 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 C

mineralization (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 (%)

Biogeochemistry (2016) 128:171–186 177

123

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 was

higher 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 lower

MB-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 was

primarily 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 from

both 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 acidic

or 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

123

(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 compound

abundance (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) and

pH (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 due

to 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), primarily

due to lower Cn/V ratios in the low lignin litter than in

Fig. 3 Microbial biomass-C (MB-C) for all genotypes in both

soil 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 (note

the 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

123

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 on

Day 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). This

suggests 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 abundance

of A polysaccharides,

B lignin derivatives, C N

bearing compounds,

D proteins, E lipids, and

F phenolic compounds in

maize 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 within

a panel as either nitrogen

(N) or pH (pH) effects, and

significant interactions

between the two (N 9 pH)

180 Biogeochemistry (2016) 128:171–186

123

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 (Klotzbucher 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 laboratory

incubation of low (A), medium (B), and high (C) lignin maize

genotypes. 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 ? Cn

units) 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

123

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 bm3

genotype. 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

123

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 NSF

Ecosystems 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

123

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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