microbial community response to nitrogen deposition in northern forest ecosystems

Microbial community response to nitrogen deposition

in northern forest ecosystems

Mark P. Waldropa,*, Donald R. Zaka, Robert L. Sinsabaughb

aSchool of Natural Resources and Environment, University of Michigan, 430 E. University Ave., Ann Arbor, MI 48109, USAbDepartment of Biology, University of New Mexico, Albuquerque, NM 87131, USA

Received 28 March 2003; received in revised form 30 January 2004; accepted 23 April 2004

Abstract

The productivity of temperate forests is often limited by soil N availability, suggesting that elevated atmospheric N deposition could

increase ecosystem C storage. However, the magnitude of this increase is dependent on rates of soil organic matter formation as well as rates

of plant production. Nonetheless, we have a limited understanding of the potential for atmospheric N deposition to alter microbial activity in

soil, and hence rates of soil organic matter formation. Because high levels of inorganic N suppress lignin oxidation by white rot

basidiomycetes and generally enhance cellulose hydrolysis, we hypothesized that atmospheric N deposition would alter microbial

decomposition in a manner that was consistent with changes in enzyme activity and shift decomposition from fungi to less efficient bacteria.

To test our idea, we experimentally manipulated atmospheric N deposition (0, 30 and 80 kg NO32-N) in three northern temperate forests

(black oak/white oak (BOWO), sugar maple/red oak (SMRO), and sugar maple/basswood (SMBW)). After one year, we measured the

activity of ligninolytic and cellulolytic soil enzymes, and traced the fate of lignin and cellulose breakdown products (13C-vanillin, catechol

and cellobiose).

In the BOWO ecosystem, the highest level of N deposition tended to reduce phenol oxidase activity (131 ^ 13 versus

104 ^ 5 mmol h21 g21) and peroxidase activity (210 ^ 26 versus 190 ^ 21 mmol h21 g21) and it reduced 13C-vanillin and 13C-catechol

degradation and the incorporation of 13C into fungal phospholipids ðp , 0:05Þ: Conversely, in the SMRO and SMBW ecosystems, N

deposition tended to increase phenol oxidase and peroxidase activities and increased vanillin and catechol degradation and the incorporation

of isotope into fungal phospholipids ðp , 0:05Þ: We observed no effect of experimental N deposition on the degradation of 13C-cellulose,

although cellulase activity showed a small and marginally significant increase ðp , 0:10Þ: The ecosystem-specific response of microbial

activity and soil C cycling to experimental N addition indicates that accurate prediction of soil C storage requires a better understanding of

the physiological response of microbial communities to atmospheric N deposition.

q 2004 Elsevier Ltd. All rights reserved.

Keywords: Phospholipid fatty acid analysis (PLFA); Phenol oxidase; Peroxidase; 13C-phenolics; 13C-cellobiose; Carbon cycling; Microbial respiration

1. Introduction

Human activity has doubled the amount of nitrogen

(N) entering terrestrial ecosystems throughout eastern

North America and Europe, a trend that is likely to

increase over the next several decades (Bouwman et al.,

2002). Because soil N availability often limits plant

growth in temperate forests, atmospheric N deposition

could increase primary production and create a sink for

atmospheric C (Townsend et al., 1996). Nevertheless, a

recent analysis of ecosystem-scale experiments estimated

that current rates of atmospheric N deposition would

globally enhance ecosystem C storage by a small margin

(i.e. 0.25 Pg C y21; sensu Nadelhoffer et al., 1999). This

estimate was based on a stoichiometric relationship

between C and N in each ecosystem pool, and it did

not consider the potential for atmospheric N deposition

to directly alter microbial physiology, and hence, the

fundamental processes controlling soil organic matter

formation.

There is good reason to suspect that atmospheric N

deposition could directly alter microbial physiology, the

degradation of plant litter, and the subsequent formation

of soil organic matter. Fog (1988) observed that

high levels of inorganic N in solution often stimulated

0038-0717/$ - see front matter q 2004 Elsevier Ltd. All rights reserved.

doi:10.1016/j.soilbio.2004.04.023

Soil Biology & Biochemistry 36 (2004) 1443–1451

www.elsevier.com/locate/soilbio

* Corresponding author. Tel.: þ1-734-763-8003; fax: þ1-734-936-2195.

E-mail address: [email protected] (M.P. Waldrop).

http://www.elsevier.com/locate/soilbio

the degradation of labile (i.e. high in cellulose) litter,

whereas it often suppressed the degradation of recalci-

trant (i.e. high in lignin) litter. This dichotomy reflects

the critical regulatory role of lignin during litter

decomposition and soil organic matter formation.

Although many fungi and bacteria produce oxidative

enzymes that modify lignin to varying degrees, white rot

basidiomycetes and xylacarious ascomycetes are primar-

ily involved with lignin degradation (Dix and Webster,

1995) and their ability to synthesize ligninolytic enzymes

is suppressed by high levels of inorganic N (Kirk and

Farrell, 1987; Hammel, 1997). These observations

suggest that atmospheric N deposition could alter

microbial physiology and decomposition in a manner

that is dependent on biochemical composition of plant

litter.

Field studies have confirmed that N deposition can

have a differential effect on litter decomposition,

depending on the initial lignin concentration of the

decomposing material. For example, Cornus florida litter

has a low lignin concentration and experimental N

deposition increased the decomposition of this material

by 50% (Carreiro et al., 2000). Conversely, experimental

N deposition reduced the decomposition of high-lignin

oak (Quercus spp.) litter by 25%. These very different

responses were consistent with changes in the activity of

extracellular enzymes involved with cellulose and lignin

degradation. Although experimental N deposition

increased the activity of cellulases (b-glucosidase,

cellobiohydrolase, and endoglucanase) in both litter

types, it increased phenol oxidase activity in C. florida

litter and decreased phenol oxidase activity in oak litter.

Because forest ecosystems differ in floristic composition

and litter biochemistry, atmospheric N deposition could

alter decomposition in an ecosystem-specific manner due

to an interaction between litter biochemistry and

extracellular enzyme production.

Our objectives were to (i) determine the influence of

atmospheric N deposition on cellulolytic and ligninolytic

enzyme activity in forest soils with contrasting litter

chemistry, and (ii) determine how atmospheric N

deposition alters the microbial metabolism of cellulose

and lignin. We reasoned that elevated atmospheric N

deposition would suppress phenol oxidase activity, thus

lessening the metabolism of lignin by soil fungi, in an

ecosystem specific manner. We addressed our objectives

in three floristically distinct forest ecosystems that range

from 0 to 100% oak in the overstory, which produced a

gradient of leaf litter lignin concentration. We measured

the activity of extracellular enzymes involved with

cellulose and lignin degradation to address our first

objective, and we addressed our second objective by

using 13C labeled products of cellulose and lignin

degradation to trace the flow of these compounds through

the soil microbial community.

2. Materials and methods

2.1. Study sites

Our study took place in three upland forest ecosystems in

northwestern Lower Michigan (Zak and Pregitzer, 1990)

These ecosystems are: the sugar maple-basswood (SMBW),

sugar maple-red oak (SMRO), and black oak-white oak

ecosystem (BOWO). In each ecosystem type, we located

three replicate stands across a two county area. Replicate

stands were separated by ca. 8 km on average. The SMBW

and SMRO ecosystems are located on soils derived from

sandy glacial till (typic haplorthods of the Kalkaska series),

whereas the BOWO ecosystem is located on coarse, sandy

glacial outwash (entic haplorthods of the Rubicon series).

These three forest ecosystems are of similar age and are

located on similar soils, but they differ greatly in above-

ground biomass, production, litter quality, and fungal:bac-

terial biomass (Table 1). Mean annual precipitation in the

study area is 81 cm, and mean annual temperature is 7.2 8C

(Zak et al., 1989).

We located three 10 £ 30 m2 plots in each stand for our

experimental N deposition treatments; each plot was

separated by at least 20 m. One plot was randomly assigned

to be the control treatment, which received only ambient

atmospheric N deposition (approx. 10 kg N ha21 y21). A

second plot was randomly selected and amended with

30 kg N ha21 y21 (low N); the remaining plot was amended

with 80 kg N ha21 yr21 (high N). Nitrogen was applied as

NaNO3 pellets, and it was mechanically broadcast within

the low and high N treatments on a monthly basis from April

through September in 2001; the treatments continue to the

present. We amended these forests with NO32 because it is

the dominant form of atmospheric N deposition in our study

area (Burton et al., 1991).

Table 1

Forest above and below-ground ecosystem properties from three northern

hardwood forest types

Black oak/white

oak

Sugar maple/

red oak

Sugar maple/

basswood

Age (yrs)a 91 (16.1)a 84 (4.2)b 83 (9.6)c

Overstory biomass

(Mg ha21)a

151 (52)a 178 (42)b 209 (38)c

Leaf litter C:Na 133 104 80

Leaf litter

production

(Mg ha21 yr21)a

1.63 (0.75)b 2.90 (0.55)a 2.36 (0.65)a

Soil C:Na 23 21 18

Fungal:bacterial

biomassb

5.0 1.1 0.83

Differences among mean values are represented by different letters.

Standard deviations are in parentheses.a From Zak and Pregitzer (1990).b Calculated from Myers et al. (2001).

M.P. Waldrop et al. / Soil Biology & Biochemistry 36 (2004) 1443–14511444

2.2. Enzyme activities

Soil samples were collected from control and high N

treatments in May, June, July, and October of 2002 for

analysis of extracellular enzyme activity. Each plot was

visually divided into quadrats and two samples were

randomly removed from each section. The soil samples

were removed with a 2-cm diameter £ 10-cm deep core,

placed in a plastic bag, and immediately transported to our

lab. Soils were removed of visible roots, and stored at

270 8C. Soil suspensions were prepared by adding 125 ml

of 50 mM sodium acetate buffer (pH 5.0) to 0.5 g soil; the

resulting suspension was homogenized using a Brinkrnann

Polytron (Brinkmann, Westbury, NY).

Phenol oxidase and peroxidase activities were deter-

mined using clear polystyrene 96-well microtiter plates

(Fisher Scientific, Pittsburg, PA) with L-3, 4-dihydroxyphe-

nylalanine (L-DOPA, 10 mM, Sigma-Aldrich, St. Louis,

MO) as the substrate. b-glucosidase activity was measured

on black polystyrene 96-well micotiter plates (Nunc, Nalge

Nunc International, Rochester, NY) using 4-methylumbel-

liferyl b-D-glucopyranoside (MUB-bG, 200 mM). Sample

suspensions (200 ml aliquots) were dispensed using eight-

channel pipetters into 16 replicate assay wells. Additionally,

we used eight wells as blanks, eight wells to determine

sample quenching, and eight well as substrate controls (i.e.

substrate but no soil suspension). Assay wells received

50 ml of the appropriate substrate, sample blanks received

50 ml acetate buffer. Quench control wells received 50 ml

MUB standard (10 mM 4-methylumbelliferone). Substrate

controls wells received 200 ml buffer and 50 ml of the

appropriate substrate. The peroxidase assay received

additional aliquots 10 ml of H2O2 (0.3%). Peroxidase

activity was calculated as the difference between the

peroxidase assay and the phenol oxidase assay.

Substrates, buffer, MUB standard and hydrogen peroxide

were dispensed using the Bio-Tek Precision 2000

(Winooski, VT). The plates were placed in an Echotherm

Chilling Incubator (Torrey Pines Scientific, Solana Beach,

CA) at 20 8C for 3–8 h. L-DOPA oxidation was measured

spectrophotometrically at 460 nm using a Molecular

Devices (Molecular Devices, Sunnyvale, CA) VERSAmax

plate reader. MUB substrate hydrolysis was monitored

using a Molecular Devices fMAX fluorometer with the

365 nm excitation—460 emission filter pair after the

addition of 10 ml 0.5 M NaOH to the wells.

2.3. Metabolism of 13C products of cellulose and lignin

degradation

Soil samples were collected in May of 2002 in all plots to

a 10 cm depth. We collected soil samples from each plot at

2-m intervals along two transects through each plot (,30

samples per plot). Samples for each plot were combined,

homogenized by hand, and kept at 4 8C for 4 d. One

microlitre of ca.14 mg C ml21 of 13C-labeled compounds

(1-cellobiose, U-vanillin, and U-catechol), was added to

12 g of field moist soil and incubated in 1 l mason jars with

airtight lids at 20 8C for 72 h. We labeled two replicate

samples from each plot with each of the 13C-labeled

compounds. One replicate was used to determine the flow of

isotope among soil pools, and the second replicate was used

to determine the amount of 13C in microbial phospholipid

fatty acids (PLFAs). One microlitre of deionized water was

added to a second set of subsamples, which served as

controls for the isotope addition experiment.

After 72 h, we removed a sample of headspace gas to

determine CO2 concentration and d 13C using a Finnigan

Delta Plus isotope ratio mass spectrometer. Following

isotopic analysis, jars were opened and one of the replicate

samples from each treatment and stand was lyophilized for

PLFA analysis. From the remaining subsamples, we

extracted dissolved organic C (DOC) by adding 20 ml of

0.5 M K2SO4. Extracts were passed through a glass fiber

filter, and the filtrate was stored at 4 8C for less than one

week. One microlitre of each filtrate was evaporated on a

hot plate, and the salt was placed in a tin capsule for

determination of total C and d13C (Bruulsema and Dux-

bury, 1996). Following DOC extraction, the soil remaining

on the glass fiber filter was placed into a vial, and the vials

were placed into a dessicator, where they were exposed to

CHCl3 vapor for seven days. The long incubation time was

used because soils were saturated. Soils were then purged

of residual chloroform, and extracted with 20 ml of 0.5 M

K2SO4. We determined microbial C in these extracts,

which were analyzed for total C and d13C as described

above. Soluble microbial carbon was converted to

microbial biomass C using the conversion factor ðkcÞ of

0.45. After microbial biomass and DOC extractions, soils

were dried at 70 8C for 4–5 d, pulverized in a ball mill, and

placed into tin capsules for total C measurement and

isotopic analysis. The metabolic quotient was calculated as

the amount of microbial respiration per unit microbial

biomass.

2.4. Microbial community composition

The effect of N treatment on soil microbial community

composition was assessed using phospholipid fatty acid

(PLFA) analysis. Five gram of lyophilized soil was

extracted using a single-phase, phosphate-buffered

CHCl3–CH3OH solvent system (White and Ringelberg,

1998). Additional chloroform and water were added to

separate aqueous and organic phases. The fatty acids in

the organic phase were fractionated on silicic acid columns

into glycolipid, neutral lipid, and phospholipids. The

phospholipids were transesterified in an alkaline system to

convert the PLFAs into fatty acid methyl esters (FAMEs).

The abundance, identification, and isotope ratios of the

PLFAs were determined by gas chromatography and isotope

ratio mass spectrometry using a Finnigan Delta Plus

IRMS interfaced with a HP 5973 gas chromatograph.

M.P. Waldrop et al. / Soil Biology & Biochemistry 36 (2004) 1443–1451 1445

We estimated microbial community composition by com-

paring the mole % of individual PLFA among our N

addition treatments. We created a fingerprint of microbial

community composition of each sample using Principal

Components Analysis (PCA) of PLFA relative abundance.

We also determined the amount of 13C in each PLFA as the

product of its 13C abundance and mass. We then compared

the quantity of label incorporated into fungal PLFAs

(18:2v6c, 18:lv9c, and 18:3v3c) and bacterial PLFAs

(i15;0, a15:0, 15:0, i16:0, 16:1v9, 16:1v7, i17:0, cy17:0,

18:1v7c, and cy19:0). We divided the total amount of

isotope in fungal PLFAs by the total amount of isotope

incorporated into bacterial PLFAs to produce a fungal:bac-

terial activity ratio.

2.5. Statistical analyses

We used a repeated-measures two-way analysis of

variance (ANOVA) to determine the influence of time,

ecosystem, and N deposition on enzyme activities. We also

used a three-way ANOVA to determine the influence of

ecosystem type, N deposition rate, and substrate type on

substrate degradation rates, fungal:bacterial activity ratio,

and the recovery of isotope in soil pools. All dependent

variables were normalized prior to analysis. A Fisher’s

protected least significant difference (LSD) was used to

compare means, and significance for analyses was accepted

at a ¼ 0:05:

3. Results

Experimental additions of N to forest ecosystems tended

to increase cellulolytic enzyme specific activity, but the

effect was only marginally significant (Fig. 1a; ecosystem £

treatment interaction p ¼ 0:07Þ: In the BOWO ecosystem,

our high N treatment produced a 20% decline in phenol

oxidase specific activity, whereas the high N treatment

resulted in a 16% increase in the SMRO and a 36% increase

in the SMBW ecosystems; these changes only marginally

significant (Fig. 1b; ecosystem £ treatment interaction p ¼

0:084Þ: Similarly, peroxidase specific activity in the BOWO

ecosystem tended to decline by 18% in the high N treatment,

but the high N treatment tended to increase the specific

activity of this enzyme by 15% in the SMRO and 26% in the

SMBW ecosystems (Fig. 1c; ecosystem £ treatment inter-

action p ¼ 0:26Þ: Nonetheless, these differences were not

significant.

Specific respiration of 13C-cellobiose did not differ

among the three ecosystem types or the control, low N,

and high N deposition treatments (Table 2). Recovery of13C-cellobiose in soil, microbial respiration, microbial

biomass, and DOC was also unaffected by N deposition

(Table 3; p . 0:05Þ: However, recovery of 13C in

the microbial biomass and DOC pools was affected

by ecosystem type ðp ¼ 0:0011 and p ¼ 0:0002Þ; where

recovery of isotope in microbial biomass was highest in the

SMRO ecosystem (8.5%), intermediate in the SMBW

ecosystem (6.6%), and lowest in the BOWO ecosystem

(5.5%; Table 3). Recovery of 13C-cellobiose in DOC was

higher in the BOWO ecosystem (0.6%), compared to the

SMRO (0.3%) and the SMBW (0.2%) ecosystems (Table 3).

Total recovery of 13C-cellobiose was low (51%). The low

recovery was due to our inability to detect label within the

relatively large soil pool. Due to a lower than expected

initial enrichment there was very little detectable label

within the soil pool, where isotope ratios were similar

between samples receiving deionized water and those

receiving the isotopically labeled cellobiose.

In contrast to cellobiose respiration, the respiration rate

of 13C-vanillin per unit microbial biomass showed a

significant ecosystem by treatment interaction (Table 2; p ¼

0:039Þ: In the BOWO soil, specific 13C-vanillin respiration

decreased by 41% in the Low N treatment and by 21% in the

High N treatment. In the SMRO ecosystem, which is

Fig. 1. Specific b-glucosidase (a), phenol oxidase (b), and peroxidase (c)

activity in the BOWO, SMRO, and SMBW forest soils. Open bars represent

control treatment plots and black bars represent the high N amended plots.

Errors bars represent 1 SE. Values represent the mean of values measured at

four time points over the summer and fall of one year. OM ¼ organic

matter.


approximately 70% sugar maple and 30% red oak, neither

the low nor the high N deposition treatment affected the

respiration of vanillin (Table 2). In the SMBW ecosystem,

respiration of vanillin in the low N deposition increased

by 46% and by 101% in the high N deposition treatment

(Table 2). Percent recovery of 13C-vanillin within the soil,

respired microbial biomass, and DOC pools was unaffected

by N deposition treatments ðp . 0:05Þ: However, the N

deposition treatments tended to enhance the label recovery

within the respired pool (ecosystem £ treatment interaction

p ¼ 0:08Þ and microbial biomass pool (ecosystem £

treatment interaction p ¼ 0:69Þ in the SMBW ecosystem

and reduce label recovery in the respired and microbial

biomass pools within the BOWO ecosystem (Table 3). More13C was recovered within the soil pool in the SMBW (68%)

than either the SMRO (51%) or BOWO (48%) ecosystems

(Table 3; p ¼ 0:0001Þ: Within the respired pool, less 13C

was recovered in the SMBW (11%) compared to the

SMRO (23%) and BOWO (24%) ecosystems ðp , 0:0001Þ:

Recovery of 13C vanillin within the microbial biomass was

also higher in the BOWO (2.1%) and SMRO (1.9%)

ecosystems compared to the SMBW (1.1%) ecosystem

(Table 3; p ¼ 0:0003Þ: However, recovery of 13C vanillin in

DOC was unaffected by either N deposition or ecosystem

type ðp ¼ 0:23Þ:

The respiration of 13C-catechol, a phenolic compound

similar to vanillin, tended to be reduced in the BOWO

ecosystem following N additions, but, like cellobiose, the

effect was not significant (Table 2; ecosystem by treatment

by substrate interaction only significant for vanillin).

However, like 13C-vanillin, 13C-cathechol respiration also

tended to increase in the SMBW ecosystem following N

additions, but the effect was not significant (Table 2). The

recovery of 13C within the soil, respiration, microbial

biomass, and DOC pools was similar to the pattern observed

with the vanillin substrate. N deposition did not affect the

recovery of 13C within any of the four measured carbon

pools; however, N deposition tended to reduce label

recovery within the respired and microbial biomass pools

in the BOWO ecosystem, and increase recovery within the

respired and microbial biomass pools in the SMBW and

SMRO ecosystems (ecosystem by treatment interaction p ¼

0:17 and p ¼ 0:41; respectively). The recovery of 13C in the

soil pool was higher in the SMBW ecosystem (84%)

compared to the SMRO (75%) and BOWO (65%)

ecosystems (Table 3; p , 0:0001Þ: Conversely, the recovery

of 13C-catechol within the respired, microbial biomass, and

DOC pools was highest within the BOWO and SMRO

ecosystems, and lowest in the SMBW ecosystem (Table 3;

all p , 0:0001).

Microbial community composition was affected by N

deposition in all three ecosystem types (Fig. 2). In the

SMBW soil, PLFAs indicative of Gram þ (a17:0),

Gram 2 (cy17:0, 18:lv5c, and 16:lv7c), and endomycor-

rhizal fungi (16:lv5c) decreased in relative abundance, but

N deposition also increased the relative abundance twoTab

le2

Th

ein

flu

ence

of

eco

syst

emty

pe

and

Nd

epo

siti

on

on

mic

rob

ial

acti

vit

yin

soil

Bla

cko

ak/w

hit

eo

akS

ug

arm

aple

/red

oak

Su

gar

map

le/b

assw

ood

Con

tro

lL

ow

NH

igh

NC

on

trol

Lo

wN

Hig

hN

Co

ntr

ol

Lo

wN

Hig

hN

13C

cell

ob

iose

resp

irat

ion

rate

(mg

exce

ss13C

–C

O2

g2

1m

icro

bia

lC

)

4.5

(0.8

)2

.6(0

.4)

3.6

(0.5

)3

.5(1

.0)

2.6

(0.5

)3

.1(0

.3)

2.9

(0.6

)3

.0(0

.3)

3.4

(0.9

)

13C

van

illi

nre

spir

atio

nra

te(m

gex

cess

13C

–C

O2

g2

1m

icro

bia

lC

)

29

.4(7

.9)a

17

.4(3

.1)d

23

.4(2

.3)b

c2

3.5

(0.9

)bc

27

.0(3

.6)a

b1

7.9

(0.3

)cd

6.7

(1.6

)fg

9.7

(3.8

)efg

13

.4(3

.8)d

e

13C

cate

chol

resp

irat

ion

rate

(mg

exce

ss13C

–C

O2

g2

1m

icro

bia

lC

)

8.8

2(2

.25

)7

.79

(1.8

)7

.47

(0.5

9)

9.2

7(1

.35

)1

0.6

(0.5

)1

0.3

(1.5

)3

.9(1

.5)

4.3

(1.8

)6

.8(4

.3)

Fungal

/bac

teri

alac

tivit

yF¼

2:6

4P¼

0:0

45

3.5

8(0

.16

)a3

.24

(0.1

8)

bc

3.1

4(0

.13

)bcd

2.8

7(0

.13

)b2

.93

(0.1

4)c

d3

.10

(0.1

5)b

cd3

.14

(0.1

5)b

cd3

.39

(0.2

5)b

c3

.42

(0.1

5)b

Val

ues

list

edar

em

eans

and

on

est

andar

dd

evia

tio

n.

Mea

ns

ina

row

wit

hth

esa

me

sup

ersc

rip

tle

tter

are

no

tsi

gn

ifica

ntl

yd

iffe

ren

t.13C

resp

irat

ion

rate

ssh

ow

eda

sig

nifi

can

tec

osy

stem

by

trea

tmen

tb

y

subst

rate

(cel

lobio

se,

van

illi

n,

or

cate

chol)

inte

ract

ionðF

¼2:2

3P¼

0:0

39Þ

Th

efu

ng

al/b

acte

rial

acti

vit

yra

tio

(see

met

ho

ds

for

calc

ula

tio

n)

isth

em

ean

for

all

thre

esu

bst

rate

s.R

ow

sw

ith

no

lett

ers

did

no

t

dis

pla

yan

ysi

gn

ifica

nt

dif

fere

nce

sam

on

gm

eans.


Gram 2 PLFAs (i16:0 and cy19:0) and the fungal PLFA

18:lv9c ðp , 0:05Þ: The response to N deposition was very

similar in the SMRO and BOWO soils, where the Gram 2

PLFA 18:lv5c and the actinomycete PLFA 10Me18:0 both

increased in relative abundance ðp , 0:05Þ: In only the

BOWO soil, the Gram þ PLFA a17:0 decreased in relative

abundance ðp , 0:05Þ: We did not observe a decrease in the

relative abundance of any fungal PLFAs in the N amended

BOWO or SMRO soils.

We calculated the ratio of fungal activity to bacterial

activity using the ratio of isotope incorporation into fungal

lipids and bacterial lipids. Although incorporation of

vanillin and catechol was, on average, 80% less than the

incorporation of cellobiose, we did not observe a significant

ecosystem £ substrate effect for the incorporation of

cellobiose, vanillin, or catechol into microbial lipids.

There was a significant decrease in fungal:bacterial activity

with N deposition in the BOWO soil and, although not

significant, the fungal:bacterial activity ratio tended to

increase following N deposition in the SMBW soil (Table 2;

ecosystem by treatment interaction p ¼ 0:045Þ:

Microbial biomass and microbial respiration were lower

in the BOWO and SMRO soils compared to the SMBW soil,

reflecting differences in soil C content (Table 4; p , 0:05Þ:

In contrast, extracted DOC was higher in BOWO

(81 ^ 21 mg kg21) and SMRO (71 ^ 15 mg kg21) soils

compared to SMBW soil (47 ^ 17 mg kg21) ðp , 0:0001Þ:

In response to one year of the high N deposition treatment,

soil C in the BOWO ecosystem increased by 34%, microbial

Table 3

Mean recovery of added label in soil, respiration, microbial biomass, and DOC pools

Substrate Ecosystem Treatment % in soil % in respiration % in microbial

biomass

% in dissolved

organic C

Total recovery

Cellobiose Sugar maple/basswood Control 8.9 (10.9) 32.1 (4.6) 6.5 (0.7) 0.1 (0.0) 47.5 (14.1)

Low N 23.3 (14.7) 33.0 (2.6) 6.2 (1.4) 0.1 (0.0) 62.6 (13.4)

High N 16.7 (3.8) 27.8 (8.4) 7.1 (1.0) 0.4 (0.2) 52.0 (8.6)

Sugar maple/red oak Control 16.0 (0.7) 29.7 (4.4) 7.5 (0.3) 0.3 (0.1) 53.5 (4.7)

Low N 8.8 (3.6) 25.7 (4.9) 9.6 (2.0) 0.3 (0.1) 44.3 (6.1)

High N 6.8 (4.5) 31.1 (4.8) 8.3 (0.5) 0.3 (0.1) 46.5 (8.7)

Black oak/white oak Control 12.6 (9.7) 35.1 (4.3) 5.5 (0.2) 0.6 (0.1) 53.6 (5.2)

Low N 15.8 (5.7) 29.7 (4.1) 5.6 (0.8) 0.6 (0.1) 51.7 (5.8)

High N 3.9 (3.0) 39.3 (3.5) 5.4 (0.9) 0.6 (0.2) 49.3 (5.1)

Vanillin Sugar maple/basswood Control 71.8 (3.6) 8.2 (0.2) 1.0 (0.0) 0.5 (0.1) 81.4 (3.7)

Low N 66.0 (6.8) 11.2 (1.3) 1.2 (0.2) 0.6 (0.0) 79.1 (5.4)

High N 66.8 (5.0) 13.4 (2.4) 1.2 (0.1) 0.5 (0.2) 81.8 (2.6)


Low N 44.3 (9.2) 27.1 (2.3) 2.1 (0.5) 0.6 (0.1) 74.1 (8.8)

High N 51.9 (6.1) 21.4 (1.7) 2.3 (0.6) 0.5 (0.1) 76.1 (6.4)


Low N 47.1 (2.6) 19.4 (4.3) 2.1 (0.2) 0.7 (0.1) 69.2 (2.5)

High N 50.0 (2.1) 24.8 (2.4) 1.8 (0.3) 0.6 (0.1) 68.8 (8.1)

Catechol Sugar maple/basswood Control 86.1 (5.6) 4.9 (0.8) 0.3 (0.0) 0.2 (0.0) 91.5 (5.8)

Low N 90.0 (13.3) 4.5 (1.5) 0.4 (0.1) 0.2 (0.0) 95.1 (12.3)

High N 76.8 (1.0) 6.1 (2.4) 0.4 (0.0) 0.2 (0.0) 83.4 (1.6)


Low N 61.8 (4.7) 11.7 (0.4) 0.9 (0.3) 0.5 (0.1) 74.9 (4.5)

High N 67.5 (0.7) 11.9 (0.7) 0.8 (0.1) 0.4 (0.1) 80.6 (0.8)


Low N 78.1 (1.8) 8.2 (0.8) 0.6 (0.1) 0.5 (0.1) 87.4 (1.6)

High N 73.8 (4.6) 7.1 (0.5) 0.5 (0.1) 0.5 (0.1) 79.5 (7.2)

Standard errors are in parentheses ðn ¼ 3Þ:

Fig. 2. Microbial community composition is altered in response to N

deposition in the three forest ecosystems. Principal components (PC1 and

PC2) were derived from mol% data of 20 individual PLFA biomarkers.

Principal component 1 incorporated 50% of the variability in the data set

and PC2 incorporated 16% of the variability in the data set. Eigenvalues for

fungal biomarkers were strongly negative for the PC1 axis.


biomass increased by 29%, and microbial respiration

increased, by 63%, but extracted DOC was not significantly

different (Table 4; p , 0:05Þ: In the SMRO ecosystem, soil

C, microbial biomass, and DOC in the low N and high N

treatments were not significantly different from the control,

but microbial respiration significantly increased by 22%

(Table 4; p , 0:05Þ: In the SMBW ecosystem, soil C was

reduced in the high N treatment by 27%, microbial biomass

was reduced by 30%, and microbial respiration was reduced

by 15% (Table 4; p , 0:05Þ: Extracted DOC in the SMBW

soil tended to decrease with greater N deposition rates from

70 mg C kg21 in the control treatment, 66 mg C kg21 in the

low N treatment, and 62 mg C kg21 in the high N treatment

ðp ¼ 0:16Þ: Lastly, the metabolic quotient (respiration per

unit microbial biomass) increased in all three soils from

133 ^ 7 mg C g21 C d21 in the control treatment of

155 ^ 7 mg C g21 C d21 in the high N treatment ðp ¼

0:023Þ:

4. Discussion

One year of experimentally elevated N deposition led

to small and marginally significant increases cellulolytic

enzyme activity, with no corresponding change in the

degradation of cellobiose. However, elevated N depo-

sition led to ecosystem-specific alterations in oxidative

enzyme activities that corresponded to patterns of fungal

activity and soil C flow. This ecosystem-specific change

in oxidative enzyme activity ultimately may have

affected soil C storage within these ecosystems (Waldrop

et al., 2004). In the BOWO ecosystem, N deposition led

to a reduction in oxidative enzyme activities, vanillin and

catechol degradation, and the ratio of fungal to bacterial

activity. Nitrogen deposition also led to increases in

oxidative enzyme activities, vanillin and catechol degra-

dation, and fungal activity within the SMRO and SMBW

ecosystems, with the magnitude of the response being

larger in the SMBW ecosystem. Thus, instead of

observing a common decline in oxidative enzyme

activities and phenolic compound degradation, the effect

was ecosystem specific. The ecosystem-specific effect of

N deposition on microbial activity, extracellular enzyme

activity, and C flow may have resulted from differences

in the fungal community composition in each ecosystem.

Most observations of a negative effect of N on phenol

oxidase activity and lignin degradation come from

studies of white-rot fungi. However, white rot fungi are

not the only organisms with oxidative enzyme activity,

and other organisms may respond differently to N

additions. For example, some soft rot species, e.g.

Aspergillus wentii, decompose lignin most rapidly when

N is abundant (Fog, 1988).

Stimulated microbial activity has been observed

following N deposition in several forest, grassland, and

wetland ecosystems (Neff et al., 2002; Pregitzer, et al.,

2002, Tietema, 1998; Arsuffi and Palm, 1996; Ohtonen,

1994); however, others have observed a repression of

microbial activity (Gallo et al., 2004; Carreiro, et al.,

2000; Smolander et al., 1994; Mcandrew and Malhi,

1992; Nohrstedt et al., 1989; Soderstrom et al., 1983),

and some have found no effect (Hobbie and Vitousek,

2000). This range of observations may be explained, in

part, by difference in microbial community composition

and their enzymatic response to N additions. The general

pattern that we observed, and the conceptual framework

to guide further research, is that ecosystems with more

recalcitrant litter contain white rot-type fungi that

respond negatively to N deposition, whereas ecosystems

with rapidly cycling litter support different fungal

populations, perhaps soft rot fungi, which respond

positively to N deposition. Consistent with this, Carreiro

et al., (2001) observed an increase in phenol oxidase

activity and litter decomposition following N fertilization

in high-quality dogwood litter and a repression of oxi-

dative enzyme activity and slower decomposition rates in

the lower-quality oak litter. Thus, our conceptual model

of oxidative enzyme regulation following N deposition

may occur over a broad spectrum of ecosystem types in

both the soil and forest floor. It will be necessary to

Table 4

Respiration rate, microbial biomass, and total soil C in control, low, and high N treatments in the three ecosystems. Standard errors are in parentheses ðn ¼ 3Þ

Black oak/white oak Sugar maple/red oak Sugar maple/basswood

Control Low N High N Control Low N High N Control Low N High N

Respiration rate

(mg C g21 soil d21)

F ¼ 3:54 p , 0:0099

24.8 (2.4)cd 28.5 (2.7)bc 40.3 (4.3)a 24.1 (1.1)d 27.0 (2.7)cd 29.2 (2.1)bc 38.8 (4.7)a 38.8 (5.0)a 32.8 (2.0)ab

Microbial biomass

(mg kg21 soil)

F ¼ 4:66 p , 0:0017

178 (6.7)d 231 (20)abc 228 (16)abc 209 (11)bcd 220 (11)abc 231 (11)abc 278 (29)a 264 (31)ab 193 (9)cd

Total C (g C kg21 soil)

F ¼ 6:4 p , 0:001

16.0 (2.8)d 19.9 (5.1)bcd 21.4 (2.7)b 17.5 (3.4)cde 15.9 (1.9)e 20.1 (1.0)bc 29.6 (4.5)a 29.4 (6.9)a 21.5 (0.6)b


quantify fungal community composition and physiology

to determine whether shifts in the abundance of white rot

and soft rot fungi are the primary cause of ecosystem-

specific response of soil C cycling to atmospheric N

deposition.

We did not observe a general decline in fungal biomass

in our N deposition treatments, but we did observe

a decrease in the abundance of an AM fungal biomarker

(16:1v5c) in the SBMW soil. Sugar maple is an AM

mycorrhizal species, and the decrease in this biomarker

following N deposition is consistent with other studies

(Boxman et al., 1998). A second fungal biomarker, 18:1v9c,

increased in relative abundance in the SMBW soil. This

biomarker is not specific to any particular fungal group, but

the trend toward higher fungal activity (relative to bacteria)

in the SMBW soil stems, in part, from this, community

dynamic.

Following our N deposition treatment, we observed

ecosystem-specific changes in microbial biomass and

microbial respiration, but these were primarily driven by

changes in soil carbon content. In turn, these changes in soil

carbon content may have been controlled by the ecosystem-

specific response of phenol oxidase activity. In the BOWO

ecosystem, phenol oxidase activity was repressed, leading

to reduced decomposition rates and a subsequent increase in

soil C. On the other hand, phenol oxidase activity increased

in the SMBW ecosystem following our N deposition

treatments, leading to more rapid decomposition rates and

a reduction in soil C. The BOWO soil gained 5.4 g kg21

carbon (a 34% increase) and the SMBW soil lost 8.1 g kg21

carbon (a 27% decrease) in the High N deposition treatment

(80 kg ha21). These changes in soil C content are roughly

twice annual leaf litterfall, thus the buildup of soil C within

the BOWO ecosystem must include belowground inputs,

the input of woody debris, litter from understory species,

and a general decline in SOM turnover. If these patterns

remain consistent over time, they represent unprecedented

changes in soil C storage due to their large magnitude over a

short time interval. Field measurement of soil carbon

content over time confirm that changes in soil carbon

occurred due to the N treatments, and differences were not

present in the treatment plots at the time the experiment

began (Waldrop et al., 2004).

Nitrogen deposition treatments led to large, rapid, and

ecosystem-dependent effect on microbial activity and soil

C cycling. These alterations most likely were driven by

ecosystem-specific microbial community responses in

oxidative enzyme activities that control C flow leading

to widely differing trajectories for soil C sequestration.

Therefore, tying the compositional and functional

responses of soil microbial communities to atmospheric

N decomposition is essential for a mechanistic under-

standing of biogeochemical cycles and accurate predic-

tions of soil C sequestration in the future.

Acknowledgements

Our work was supported by grants form US Department

of Energy’s Office of Science, Biological and Environment

Research (BER). Bill Holmes, Matt Tomlinson, and Rachel

Ammonette provided critical assistance in the field and

laboratory, and we sincerely thank them.

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