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Nitrogen fertilization directly affects soil bacterial diversity and
indirectly affects bacterial community composition
Jun Zeng
a
, Xuejun Liu
b
, Ling Song
b
, Xiangui Lin
a
, Huayong Zhang
a
, Congcong Shen
a
,
Haiyan Chu
a
,
*
a
State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, East Beijing Road 71, Nanjing 210008,
PR China
b
College of Resources and Environmental Sciences, Key Laboratory of PlanteSoil Interactions of the Ministry of Education, China Agricultural University,
Beijing 100193, PR China
article info
Article history:
Received 9 April 2015
Received in revised form
17 September 2015
Accepted 27 September 2015
Available online 13 October 2015
Keywords:
Above- and below-ground interactions
Bacteria
Biodiversity
Nitrogen fertilization
Grassland
Pyrosequencing
abstract
Nitrogen (N) deposition influences both above- and below-ground communities and influences
ecosystem functioning. However it is not clear about direct or indirect interactions among plants, soils
and microbes in response to nitrogen deposition. In this study, the responses of soil bacterial diversity to
N enrichment were investigated at surface (0e10 cm) and sub-surface (10e20 cm) soils in a temperate
steppe ecosystem. N addition (>120 kg N ha
1
yr
1
) resulted in a significant shift in bacterial community
composition and a decrease in bacterial OTU richness in surface soil, but the effect on the sub-surface
layer was far less pronounced, even at the highest addition rate (240 kg N ha
1
yr
1
). Bacterial OTU
richness was significantly correlated with soil and plant characteristics. Hierarchical structural equation
modeling showed that soil ammonium availability was responsible for the shift in bacterial richness,
whereas the change in bacterial community composition was due to alterations in soil pH and plant
composition. These results indicated that N fertilization directly affected soil bacterial richness but
indirectly affected bacterial communities through soil acidification and plant community change, indi-
cating distinct controls on soil bacterial diversity and community composition. Our results also suggest
that N availability could be a good predictor for the loss of soil bacterial diversity under atmospheric
nitrogen deposition.
©2015 Elsevier Ltd. All rights reserved.
1. Introduction
Atmospheric nitrogen (N) deposition that mainly originates
from anthropogenic activity has increased three to five-fold over
the past century (Denman et al., 2007), and the deposition rate of N
is predicted to double by 2050 (Galloway et al., 2004; Phoenix et al.,
2011). In China, atmospheric N deposition has increased by
8kgNha
1
since the 1980s (Liu et al., 2013) and has become a
matter of great concern to the potential impact on ecosystem
structure and function including eutrophication, soil acidification
and the loss of biodiversity (Vitousek et al., 1997; Guo et al., 2010).
Elevated N inputs usually increase above-ground plant production
in terrestrial ecosystems, with corresponding changes in plant
community composition and, in most cases, decreased plant
diversity, decreased lignin in leaf litter, and influence on N ratio and
carbon (C) substrates that directly stimulate heterotrophic respi-
ration (Phoenix et al., 2011). These above-ground alterations cause
a ripple of changes that affect the soil C pool that contributes to the
global C budget and climate change.
It is well known that many soil microbes are directly related to
soil biogeochemical processes and play a prominent role in the soil
C cycle (Bardgett et al., 2008). However, the mechanisms underly-
ing the soil microbial feedback in response to global climate change
remain elusive. A number of studies have reported negative effects
on microbial activity as a result of N amendment, which may
culminate in a decrease in the rate of soil respiration and an in-
crease in C sequestration (Liu and Greaver, 2010). The microbial N
mining hypothesis predicts that soil microbes use labile C to
decompose recalcitrant organic matter to facilitate N acquisition,
but this process is suppressed by increasing N availability that leads
to a decrease in microbial activity (Craine et al., 2007). The enzyme
inhibition hypothesis proposes that the enzymes involved in
*Corresponding author. Tel.: þ86 2586881356; fax: þ86 02586881000.
E-mail address: hychu@issas.ac.cn (H. Chu).
Contents lists available at ScienceDirect
Soil Biology & Biochemistry
journal homepage: www.elsevier.com/locate/soilbio
http://dx.doi.org/10.1016/j.soilbio.2015.09.018
0038-0717/©2015 Elsevier Ltd. All rights reserved.
Soil Biology & Biochemistry 92 (2016) 41e49
decomposing recalcitrant C are inhibited by N addition, thereby
reducing overall microbial activity (Gallo et al., 2004). Besides
changes in microbial activity, N fertilization also induces alteration
in soil microbial community composition. Fierer et al. (2007)
observed that shifts in the specific community were responsible
for the decrease in decomposition rate, that an N addition
decreased the relative abundance of oligotrophs that are adept at
catabolizing recalcitrant C. However, the microbial responses to
elevated N inputs are frequently mixed and lack consistency. For
instance, Fierer et al. (2012) found that N enrichment led to sig-
nificant decrease in bacterial phylotype diversity in an agricultural
field but had no effects in grassland, suggesting that the effects of N
fertilization on bacterial diversity are likely site-dependent.
The influences of N enrichment on soil microbial community
diversity may be caused by direct effects of N as a nutrient, or by
indirect changes in soil and plant properties. Soil microbes could
promote plant diversity by increasing the diversity of available
nutrient pools, whereas plant diversity can promote soil microbial
diversity by increasing diversity of food resources and diversity of
plant hosts for symbiotic and pathogenic microbes (Klironomos
et al., 2011). Ramirez et al. (2010b) reported consistent responses
in microbial respiration to N addition regardless of soil type and N
form, suggesting that the response was resulted from direct effects
by N availability, rather than indirect effects such as soil pH. By
contrast, results in Wess
en et al. (2010) showed that alteration in
bacterial abundance affected by different fertilization regimes
(including ammonium sulfate fertilization) was mainly driven by
soil pH. Weand et al. (2010) also concluded that the microbial
response to N addition was tree species-specific due to qualitative
differences in plant-derived C. Therefore, alterations in soil, plant
and microbe following N enrichment never occur in isolation, and a
whole system approach revealing direct or indirect effects is
needed for understanding the mechanisms underlying these
ecological responses and feedbacks.
It was shown that a range of edaphic factors including pH,
nutrient and O
2
levels varied with soil depth, and these differences
result in distinct microbial communities along soil profiles (Fierer
et al., 2003; Eilers et al., 2012). N fertilization affects soil parame-
ters in both surface and sub-surface soil layers, and influences the
distinct responses of soil microbial communities. Experiments have
been conducted on a temperate steppe located at Duolun County in
Inner Mongolia, China, in an area that is sensitive to climate change,
overgrazing and nutrient supply, but the effects of N deposition
were not focused upon (Liu et al., 2011). In the present study, we
investigated response of soil bacterial community composition and
diversity under different levels of N fertilization, and explore the
effects of N enrichment on plantesoilemicrobe system and the
interactions among these components using a path-relation
network and structural equation modeling. In addition, surface
and sub-surface soil samples were collected for comparison of
alteration in bacterial diversity between the two soil layers. As a
consequence of layer-specific driving forces, it was hypothesized
that bacterial composition would vary along the N addition
gradient in the two layers.
2. Experimental procedures
2.1. Study sites and experimental design
This study was conducted in a grassland fertilization experi-
mental field at Duolun County in Inner Mongolia, China (DL;
temperate steppe; 42
02
0
N, 116
17
0
E, 1324 m a.s.l.). The climate of
the station is a typical temperate continental monsoon, with a
warm and dry summer, and long and cold winter. Mean annual
temperature is 2.1
C, and precipitation is 386 mm, with 91% falling
from May to October. The experimental field was fenced off to
prevent grazing disturbance, and a randomized block design was
used, as detailed in Song et al. (2011). The N gradient was estab-
lished in 2005, at rates of 0, 60, 120 and 240 kg N ha
1
yr
1
using
NH
4
NO
3
(except urea was applied in 2005), with five replicate plots
in each treatment. N was added to the plots three times for foliar
applications in June, July and August.
2.2. Sampling and analysis
Soil samples were collected on 16 June 2011 before N addition,
at depths of 0e10 cm (n ¼20; designated N0 to N240) and
10e20 cm (n ¼20; N0b to N240b). Samples were transported on ice
and stored at 4
C for soil measurements and 40
C for genomic
DNA extraction. Soil pH was measured using a pH meter with a 1:5
(wt/vol) ratio of soil to water following shaking for 30 min. Soil total
carbon (TC) and total nitrogen (TN) were measured with a CN
Analyzer (Vario Max CN, Elementar, Hanau, Germany). Nitrate
(NO
3
eN), ammonium (NH
4
þ
eN), dissolved organic carbon (DOC)
and dissolved total N (DTN) were extracted from 10 g soil using
2 mol L
1
KCl extraction procedures. NO
3
eN, NH
4
þ
eN and DTN
content was determined using a San
þþ
Continuous Flow Analyzer
(Skalar, Breda, The Netherlands), and DOC was determined using a
Multi N/C 3000 Analyzer (Analytik Jena AG, Thuringia, Germany).
Dissolved organic nitrogen (DON) was calculated according to the
following formula: DON ¼DTN NH
4
þ
eNNO
3
eN.
Plant sampling was performed on the 20th and 21st August in
2011 at maximum sward biomass; all sampling methods except
plant biomass determination were performed nondestructively.
Plant community coverage and richness were determined by visual
estimates. Briefly, one permanent quadrat (1 1 m) was estab-
lished at each subplot, and a frame (1 1 m) with 100 equally
distributed grids spaced 10 cm apart was placed above the canopy
in each quadrat. The percentage cover of each species was esti-
mated visually in all grid cells. Species richness was defined as the
number of different species in one quadrat. Above-ground vege-
tation was sampled by clipping all plant species at the soil surface. A
quadrat (1 1 m) was placed within each plot randomly, but
overlap with the permanent quadrat was avoided, as was place-
ment within 50 cm from the edge of the plot to avoid edge effects.
Plant samples were oven dried for 48 h at 65
C and weighed. Plant
N concentration was determined by micro-Kjeldahl digestion and
continuous flow stable isotope ratio mass spectrometry (Delta Plus,
Finnigan, Pittsburgh, PA, USA). Forbs, legumes and grasses were
collected and analyzed as appropriate.
2.3. Barcode pyrosequencing of the 16S rRNA gene
DNA in each sample was extracted from ~0.5 g soil using the
FastDNA SPIN Kit for soil (MP Biomedicals, Santa Ana, CA, USA) and
purified using the UltraClean Soil DNA Kit (MOBIO Laboratories,
Carlsbad, CA, USA) following the manufacturer's instructions. The
16S rRNA gene was amplified in triplicate using a barcoded primer
set 515f/907r targeting a region suitable for phylogenetic infor-
mation (Biddle et al., 2008), and samples were pooled and purified
using an EasyPure Quick Gel Extraction Kit (Transgen, Beijing,
China). After quantification by NanoDrop ND-100 (Thermo Scien-
tific, Waltham, MA, USA), equimolar concentrations of purified
amplicons were pooled into a single tube before sequencing on a
Roche FLX 454 pyrosequencing machine (Roche Diagnostics Cor-
poration, Indianapolis, IN, USA).
In order to obtain high-quality sequences, raw sequence data
was passed through quality filters to reduce the error rate using
MOTHUR v. 1.30.2 (Schloss et al., 2009). Briefly, reads containing
ambiguous bases, those shorter than 200 bp, or not perfectly
J. Zeng et al. / Soil Biology & Biochemistry 92 (2016) 41e4942
matching the forward primer or the barcode were removed. After
trimming the primers and barcodes, potential chimeric sequences
were identified and removed using UCHIME (Edgar et al., 2011). The
remaining reads were aligned and classified using the SILVA
reference database for bacterial sequences (Pruesse et al., 2007).
Contaminants not belonging to domain bacteria were subsequently
eliminated. Operational taxonomic units (OTUs) were built by
generating a distance matrix with pairwise distance lengths
smaller than 0.3, and the sequences were then clustered and each
OTU was classified. Global singletons (i.e., OTUs represented by
only one sequence) were excluded from the database to down
weigh the effects by rare species, and the final total was 89,129
quality sequences with between 71 and 3390 reads per sample
(Table S1). All downstream analyses were performed after samples
were rarified to 1568 sequences per sample, to correct for differ-
ences in sequencing effort and to guarantee at least three replicates
in each treatment; five samples were excluded from further anal-
ysis due to insufficient effective reads (Table S1). To identify
changes in bacterial diversity, rarefaction curves of phylotype
richness (number of unique OTU) and phylogenetic diversity
(Shannon index, H
0
) were obtained using MOTHUR, with 1000
resampling at 200 sequence intervals.
2.4. Statistical analysis
To compare the differences in bacterial abundance among the N
treatments, the data of bacterial abundance was log transformed to
meet the requirement of normal distribution and homogeneity of
variance. Differences within N treatments were assessed by un-
paired Student's t-test or One-way ANOVA. The Response Ratio (RR)
(Luo et al., 2006) was employed to illustrate the changes in bacterial
relative abundance, and non-metric multidimensional scaling
(NMDS) ordination plots were used to display differences in bac-
terial community composition. Three non-parametric multivariate
statistical methods were used to examine the effects on bacterial
communities of N addition, including analysis of similarities
(ANOSIM) (Clarke, 1993), non-parametric multivariate analysis of
variance (adonis) (Anderson, 2001), and multiple response per-
mutation procedure (MRPP) (Mielke and Berry, 2001).
Distance-based multivariate analysis (DistLM) (McArdle and
Anderson, 2001) was implemented to determine the influence of
environmental variables on bacterial community diversity, based on
the resemblance matrix generated using BrayeCurtis similarity on
the presence/absence of the OTUs within each sample. Marginal
tests were applied to assess the statistical significance and per-
centage contribution of each variable in isolation, and sequential
tests were performed to evaluate the cumulative effect of environ-
mental variables. Structural equation modeling (SEM) (Grace, 2006)
was used to gain a mechanistic understanding of how soil and plant
properties mediate alterations in soil bacterial composition and
diversity under N enrichment conditions. The community compo-
sition (beta diversity) of plants and microbes was obtained by
Principal Component Analysis (PCA), and the first principal com-
ponents (PC1) were used in the subsequent SEM analysis. SEM
analysis was performed with the specification of a conceptual
model of hypothetical relationships (Fig. S1), assuming N addition
alters edaphic factors and plant community composition, which in
turn affects microbial community composition and diversity. In SEM
analysis, we compared the model-derived varianceecovariance
matrix against the observed varianceecovariance matrix, and data
were fitted to the models using the maximum likelihood estimation
method. Adequate model fits were indicated by the
c
2
test (df >5;
P>0.05) and a low RMSEA (<0.05) (Wei et al., 2013). The final model
was improved by removing relationships between observed vari-
ables from prior models based on these indices (Table S2).
Analyses were performed using SPSS software v. 11.5 (SPSS Inc.,
Chicago, IL) and the vegan and sem packages in R v.2.8.1. DistLM
analysis was performed using the computer program DISTLM_for-
ward3 (Anderson, 2003).
2.5. Accession numbers
The 16S amplicon sequences were deposited in European
Nucleotide Archive (ENA) under the accession number PRJEB8961.
3. Results
3.1. Effects of N addition on plant and soil parameters
After a six-year N fertilization regimen, plant productivity was
estimated by measuring the above-ground biomass, which was
stimulated significantly by N addition, but this was accompanied by
a sharp decrease in species richness. An increase in plant N con-
centration was frequently observed, and various plant properties
including relative coverage and average height were affected by N
enrichment (Table S3), as detailed in Song et al. (2011).
N addition markedly affected most of the measured soil prop-
erties in the surface layer, but had a much less pronounced effect on
the sub-surface layer (Table S4). In the uppermost 0e10 cm layer,
soil dissolved inorganic N (NH
4
þ
eN and NO
3
eN) was generally
correlated with the N gradient, from 13.45 to 98.51 mg kg
1
, which
is accompanied by a corresponding decrease in soil pH (7.19e4.68).
In contrast, dissolved inorganic N in the 10e20 cm layer was much
less affected (9.94e27.92 mg kg
1
), mainly due to the increased
NO
3
eN content (from 5.81 to 22.84 mg kg
1
) that likely resulted
from a difference in the rate of leaching of NO
3
eN and NH
4
þ
eN. A
small but statistically significant change in soil pH was observed in
the 10e20 cm layer. N addition induced significant changes in DON
in the top 0e10 cm layer while had less effects on soil TC and TN.
3.2. Changes in the composition of the bacterial community in
response to N addition
The bacterial composition was dominated (5%) by Actino-
bacteria (44.2%), Alphaproteobacteria (14.3%), Acidobacteria (6.6%),
and Firmicutes (7%) across all 32 samples analyzed, but other taxa
were present at lower abundance (Fig. 1 &Table S5). Unpaired
Student's t-tests revealed a strong shift in bacterial abundance at a
depth of 0e10 cm, with 7 bacterial phyla significantly affected by N
addition. In contrast, only one bacterial phylum showed significant
changes in the 10e20 cm layer (Table S6). The dynamic responses in
the top soil layer were further illustrated by the response ratio,
which showed that most of the bacterial taxa affected were rela-
tively rare (abundance lower than the median value), and the
response was usually dose-dependent regarding N addition (Fig. 2).
Specifically, in the class or phylum level, Acidobacteria, Alphapro-
teobacteria, Bacteroidetes, and Chloroflexi decreased following N
enrichment, while Actinobacteria and Betaproteobacteria exhibited
the opposite trend. Interestingly, bacterial taxa belonging to the
same group did not always respond in a similar manner. For
example, Acidimicrobidae with less abundance responded in an
opposite manner to other bacterial taxa within the phylum Acti-
nobacteria. Clearly, the response of bacterial group is determined
by the abundance of taxa at the lower taxonomic level. However,
some minor changes at the lower taxonomic level were not always
displayed at the higher level, possibly due to the low abundance in
those changed taxa. For example, changes in Bacilli belonging to the
phylum Firmicutes and Myxococcales belonging to the sub-phylum
Deltaproteobacteria did not result in the corresponding changes in
Firmicutes and Deltaproteobacteria, respectively (Fig. 2).
J. Zeng et al. / Soil Biology & Biochemistry 92 (2016) 41e49 43
Differences in the overall bacterial composition were assessed
based on pyrosequencing data, and a relatively small BrayeCurtis
distance is indicative of a similar bacterial community. BrayeCurtis-
based NMDS revealed that soils from the two depths harbored
distinct bacterial communities (Fig. 3a), but only the top 0e10 cm
layer underwent a significant shift in bacterial composition upon N
addition (Fig. 3b). An N addition rate of 120 kg N ha
1
yr
1
or greater
was required for a significant shift to occur, and this was confirmed
by non-parametric multivariate statistical tests including ANOSIM,
ADONIS and MRPP (Table S7). DistLM analysis of the 0e10 cm depth
soil revealed that most of the measured environmental factors were
correlated with bacterial community composition when considered
individually (Table 1a); soil pH (16.92%) and forb N content (14.87%)
were the most closely correlated soil and plant factors, respectively.
The sequential model indicated that soil and plant factors individ-
ually accounted for 23.18% and 21.4% of the total variation (Table 1b),
Fig. 1. Relative abundance of bacterial group under different N addition treatments. The group accounting for 1% are shown while those <1% are integrated into ‘other’.
Fig. 2. Significantly altered bacterial taxa (1%) in the uppermost 0e10 cm soil layer following N fertilization as measured by the response ratio method at the 95% confidence
interval. Bacterial taxa in brackets exhibited identical changes at the lower taxonomic level. Colors points indicate different N addition rates, while Gray points indicate no sig-
nificant changes (P>0.05; unpaired t-test) compared with controls. Relative abundance for each phylotype in the controls is listed on the right (taxa in different group was labeled
in different colors; the break is based on the median value of relative abundance).
J. Zeng et al. / Soil Biology & Biochemistry 92 (2016) 41e4944
and no additional was accounted for when factors were considered
simultaneously (Table S8), suggesting that the variables overlap in
their explanatory capacity.
3.3. Bacterial OTU richness and diversity
N fertilization had a negative impact on bacterial richness and
diversity in the top 0e10 cm soil layer (Fig. 4), but had a less pro-
nounced effect on the 10e20 cm depth soil (data not shown).
Although the rarefaction curves did not plateau, the coverage of
each sample at selected size (1568 sequences) approached 80%
(Table S1). In the 0e10 cm depth soil, NH
4
þ
eN(r¼0.94) was most
strongly correlated with phylotype richness and phylogenetic di-
versity for bacterial communities, and bacterial diversity was also
closely correlated with soil pH (r ¼0.88) and NO
3
eN(r¼0.8;
Fig. 5,Table S9). In addition, a correlation was also observed
between plant and bacterial composition, for both beta diversity
(community composition; r ¼0.836) and phylotype richness
(r ¼0.652 in Fig. 6). These results emphasize the positive rela-
tionship between above- and below-ground ecosystems.
3.4. Integrated responses of plantesoilemicrobe systems
The integrated responses of the overall plantesoilemicrobe
system were investigated using the SEM model, which can reveal
the concerted responses of soil, plants and bacteria following N
addition. The improved model proved a good fit to the data
(
c
2
¼11.84; P¼0.419), and accounted for 96% of the variation in pH,
79% and 88% in NO
3
eN and NH
4
þ
eN, 61% and 70% in plant com-
munity composition and richness, and 94% and 91% in microbial
community and richness, respectively (Fig. 7). Overall, N addition
significantly affected structure of both plant and bacterial
Fig. 3. Effect of N fertilization on soil bacterial community composition. (a) Non-metric multidimensional scaling (NMDS) ordination plot of soil microbial community structure
based on the number of OTUs detected by pyrosequencing. (b) BrayeCurtis distance differences between N treatments and controls. Pvalues are based on the unpaired Student's t
test. **P<0.01.
Table 1
DistLM analysis of multivariate species data from the uppermost 0e10 cm soil layer and plant parameters for (a) each variable taken individually and (b) variables combined in
sequence.
Variable % Var F PVariable % Var F PCum. (%)
(a) Variables individually (b) Variables fitted sequentially
Soil parameters
pH 16.92 3.2585 0.001 pH 16.92 3.2585 0.001 16.92
NH
4
þ
eN 16.32 3.1203 0.001 TC 6.26 1.2219 0.014 23.18
NO
3
eN 14.83 2.785 0.001 NH
4
þ
eN 5.93 1.1713 0.113 29.11
DON 11.48 2.0758 0.002 C:N 5.47 1.087 0.353 34.58
TC 8.19 1.4277 0.048 Moisture 5.28 1.0538 0.425 39.86
TN 6.84 1.1747 0.152 DON 4.92 0.9799 0.563 44.78
C:N 6.28 1.0718 0.24 TN 4.89 0.971 0.538 49.67
Moisture 5.46 0.9239 0.552 NO
3
eN 4.89 0.9689 0.555 54.56
DOC 4.46 0.7476 0.993 DOC 4.34 0.8454 0.683 58.9
Plant parameters
Forb nitrogen 14.87 2.7957 0.001 Forb nitrogen 14.87 2.7957 0.001 14.87
Grass coverage 14.69 2.7541 0.001 Forb coverage 6.53 1.2454 0.043 21.4
Grass height 14.46 2.7051 0.002 Legume nitrogen 5.83 1.1215 0.218 27.23
Forb coverage 14.35 2.6805 0.001 Legume coverage 5.61 1.0864 0.369 32.84
Grass biomass 14.03 2.6107 0.001 Legumes height 5.87 1.1491 0.239 38.71
Total biomass 13.59 2.5172 0.002 Grass height 5.75 1.1393 0.307 44.46
Total height 12.77 2.3432 0.001 Grass biomass 5.24 1.0411 0.452 49.7
Grass nitrogen 11.03 1.9828 0.004 Grass nitrogen 5.11 1.0183 0.475 54.81
Total nitrogen 9.96 1.7693 0.005 Total nitrogen 5.34 1.0722 0.429 60.15
Legume nitrogen 9.89 1.7556 0.004 Grass coverage 4.95 0.9935 0.499 65.11
Legume coverage 8.45 1.4759 0.032 Forb biomass 5.09 1.0243 0.439 70.19
Forb biomass 7.34 1.2666 0.096 Total biomass 5.99 1.2583 0.307 76.19
Legumes height 6.13 1.0449 0.282 Legume biomass 5.14 1.1006 0.393 81.32
Forb height 5.77 0.9795 0.409 Total height 4.76 1.0272 0.449 86.09
Legume biomass 5.71 0.9689 0.449 Forb height 4.4 0.9254 0.478 90.49
%Var: percentage variance in species data explained by that variable; Cum. %: cumulative percentage of variance explained.
Significant (P<0.05) values were shown in bold.
J. Zeng et al. / Soil Biology & Biochemistry 92 (2016) 41e49 45
communities due to increased NO
3
eN and NH
4
þ
eN and decreased
soil pH. Increases in NH
4
þ
eN and NO
3
eN content directly diminish
bacterial and plant richness, respectively, while soil acidification
was responsible for altering plant and bacterial community
composition. In addition, alterations in the plant community
resulted in concomitant shifts in bacterial community composition.
The relationships between other variables were not of great sig-
nificance on their own, but they clearly improved the model when
incorporated together (Table S2).
4. Discussion
Changes in soil bacterial community composition associated
with changes in quantity and quality of soil organic matter are
likely to subsequently influence soil C storage (Cusack et al., 2011).
In addition, the loss of species diversity following N enrichment
may threaten to ecosystem stability and affect interactions between
above- and below-ground ecosystem (Tilman et al., 2006). The in-
teractions among plants, soils and microbes play a critical role in
nutrient cycling, and the incorporation of microbial community
into ecosystem model is necessary for predicting ecosystem pro-
cess (Allison and Martiny, 2008; Miki et al., 2009). However, earlier
studies about the effects of N fertilization on soil microbial com-
munities did not include plant community data, often neglecting
the interactions between above- and below-ground communities.
Thus, understanding the direct or indirect interactions among
plants, soils and microbes is necessary to assess the effects of N
enrichment on ecosystem functioning. In this study, we found that
N fertilization resulted in significant changes in bacterial commu-
nity composition and the loss of bacterial diversity in surface soil.
We further found that N fertilization directly affected bacterial di-
versity by increasing soil ammonium availability while indirectly
affected bacterial community composition by soil acidification and
plant community change (Fig. 7).
In the present study, N fertilization resulted in the decrease of
both bacterial and plant diversity, which is consistent with previous
studies showing a decline in microbial diversity following N
enrichment (Campbell et al., 2010). It was reported that N accu-
mulation causes a decline in biodiversity by stimulating the
expansion of nitrophilous species and competitive exclusion of
others (Bobbink et al., 2010). A positive interaction between plant
and bacterial diversity was apparent (Fig. 6), consistent with the
theory that plant diversity enhances the diversity of soil microbes by
increasing the range of food resources available (van der Heijden
et al., 2008). Previous studies indicated that microbial responses
to N addition were tree species-specific, and changes in plant
composition may influence the microbial community via altering
the quality of plant-derived C, particularly the percentage of recal-
citrant compounds (Weand et al., 2010; Sagova-Mareckova et al.,
2011). Strickland et al. (2009) showed that bacterial communities
sharing a common history with a given foliar litter exhibited higher
decomposition rates compared with those from elsewhere, illus-
trating the role of plants and plantemicrobe interactions in deter-
mining the composition of the bacterial community. The model also
revealed the crucial roles of soil pH and ammonium availability in
determining bacterial community composition and diversity
following N enrichment. Soil bacterial composition is frequently
reported to be correlated with soil pH, even at large scales, and a
narrow pH range for optimal growth of bacteria may be the primary
factor influencing bacterial community composition (Lauber et al.,
2009; Rousk et al., 2010). In addition, soil acidification can result
in changes in nutrient availability, such as calcium and magnesium
(Lucas et al., 2011), and mobilization of the toxic mineral aluminum
(Aber et al., 1998), which may indirectly affect soil microbial com-
munities. Although soil acidification was deemed as the main driver
in different soil management and land-use types (Lauber et al.,
2008; Wess
en et al., 2010), elevated N availability in response to N
fertilization can directly affect soil bacterial community composi-
tion. Ramirez et al. (2010b) observed consistent effects of nitrogen
fertilization on microbial respiration regardless of soil and N fer-
tilizer type. However, other factors may also contribute to soil mi-
crobial community changes in response to nitrogen enrichment.
Cusack et al. (2011) found that the shifts in quantity and quality of
soil organic matter following N enrichment were linked with
changes in soil microbial community and the associated enzyme
activities. In addition, soil CEC has been found to strongly contribute
to variation in soil bacterial community as soil CEC influenced the
sensitivity to soil acidification and the capacity for nutrient cation
retention (Clark et al., 2007). Indeed, soil (23.18%) and plant (21.4%)
factors made approximately equal contributions to the variation
(Table 1), but did not provide any additional explanation of the
variation when considered together (Table S8). This suggests that
some of the variables within these categories are themselves
correlated and overlap in their explanatory power under N enrich-
ment conditions, and the contribution of individual factors cannot
be deconvoluted definitively.
Sequencing analysis indicated consistent general phylum-level
responses associated with N addition in the uppermost 0e10 cm
of soil (Fig. 2). Acidobacteria, Alphaproteobacteria, Bacteroidetes,
and Chloroflexi generally decreased in abundance, while Actino-
bacteria and Betaproteobacteria increased. Shifts in bacterial
composition following N manipulation were previously explained
by the copiotrophic hypothesis, in which copiotrophic groups (e.g.
Actinobacteria and Firmicutes) that have fast growth rates are more
likely to increase in nutrient-rich conditions, while oligotrophic
Fig. 4. Rarefaction curves of phylotype richness (a) and phylogenetic diversity
(Shannon's index, H0) (b) for bacterial communities in the uppermost 0e10 cm soil
layer. Insets show differences in bacterial richness and diversity under N input con-
ditions, after normalizing the number of sequences to 1568. Different letters indicate
significant differences among treatments (P<0.05, ANOVA).
J. Zeng et al. / Soil Biology & Biochemistry 92 (2016) 41e4946
groups (e.g. Acidobacteria and Chloroflexi) that have a slower
growth rate would likely decline (Fierer et al., 2007). This shift is
consistent with the microbial N mining hypothesis, which suggests
that soil microbes reduce decomposition of recalcitrant C in
response to lowered N requirement and lead to a shift towards
labile C decomposition under N enrichment condition (Craine et al.,
2007). However, some copiotrophic organisms such as the
Alphaproteobacteria did not increase in abundance following N
addition (Fig. 2). This varied response was also observed in Fierer
et al. (2012) that N enrichment led to increase in abundance of
the Alphaproteobacteria in a grassland, but had no significant effect
in an agricultural field. The response ratio indicated that phylum or
class-level responses were mainly determined by the abundance at
a lower taxonomic level, since not all bacterial taxabelonging to the
same group shifted in a similar manner. Thus, it appears to be more
reasonable to assess the response of bacterial communities at a
lower taxonomic level. Also, noted that microbial responses were
frequently inconsistent, and the response was affected by both the
amount of N added and the duration of the treatment (Janssens
et al., 2010). A low rate of N input did not cause a significant
response in bacterial community composition in either soil depth
(Fig. 3), which is in line with Fierer et al. (2012) that phylogenetic
and metagenomic shifts were most pronounced at the highest N
input, while an intermediate level of N addition did not lead to a
significant shift in the bacterial community.
Bacterial diversity clearly declined with increasing N addition
rate (Fig. 4), consistent with the finding in Campbell et al. (2010).
Our results also indicated that availability of ammonium rather
than nitrate was mainly responsible for alteration in bacterial di-
versity (Fig. 7). For example, although soil nitrate content in sub-
surface layer was quite high (22.84 mg kg
1
) at the highest input
rate, bacterial diversity was little affected (Table S4). The decline in
bacterial diversity may also be a result of competitive exclusion due
to the loss of plant species diversity by increasing N availability
(Phoenix et al., 2011). Ramirez et al. (2010a) showed that N
enrichment led to an inconsistent effect on microbial diversity at
two experiment field, and they speculated that soil pH controlled
microbial diversity. Soils with near-neutral pH usually have a
higher phylogenetic diversity than acidic or basic soils (Lauber
et al., 2009). However, soil pH is not the only factor affecting bac-
terial diversity, since soil type (Griffiths et al., 2011), moisture
(Cruz-Martínez et al., 2009), crop rotation (Lupwayi et al., 1998),
and nitrogen content (Fierer et al., 2012) have all been shown to
play a part. Fierer et al. (2012) observed that N enrichment led to
decrease in plant diversity while had no effect on bacterial di-
versity, suggesting that the controls on plant diversity and bacterial
diversity may not be the same. However, in our study, the positive
correlation between plant and bacterial diversity indicates that
they may be affected jointly by nitrogen enrichment (Fig. 6). Prober
et al. (2014) found that soil bacterial beta diversity could be pre-
dicted by plant beta diversity, while alpha diversity could not be
predicted across a global range of temperate grasslands. However,
the interactions of plant and microbe might be weakened under N
enrichment condition (Wei et al., 2013).
Changes in microbial activity and community composition can
be directly related to alterations in biogeochemical processes. Our
results showed that bacterial community composition was signifi-
cantly altered by N fertilization, which appeared to be mediated
largely by soileplantemicrobe interactions. Specifically, nitrogen
fertilization directly affected soil bacterial diversity by increasing
Fig. 5. Diversity (number of phylotypes and Shannon's index H0) of soil bacteria in relation to soil pH (a, b), nitrate (c, d) and ammonium (e, f) in the uppermost 0e10 cm soil layer.
J. Zeng et al. / Soil Biology & Biochemistry 92 (2016) 41e49 47
soil N availability while indirectly affected bacterial community
composition through soil acidification and plant community
change. Decrease in biodiversity induced by N deposition may pose
a serious threat to ecosystem stability. Our results suggest that soil
nitrogen availability could be a good predictor for the loss of bac-
terial diversity under atmospheric nitrogen deposition.
Acknowledgments
We thank Yingying Ni and Huaibo Sun for their assistance in the
lab, and Jinbo Xiong, Yu Shi, Xingjia Xiang, Dawei Ma, Ruibo Sun,
Yuntao Li, Teng Yang and Kaoping Zhang for their assistance in data
analysis. This work was supportedby the Strategic Priority Research
Program of the Chinese Academy of Sciences (XDB15010101), the
National Program on Key Basic Research Project (2014CB954002)
and the National Natural Science Foundation of China (41371254).
Appendix A. Supplementary data
Supplementary data related to this article can be found at http://
dx.doi.org/10.1016/j.soilbio.2015.09.018.
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