Impacts of urea N addition on soil micro

Plant Soil (2008) 311:19–28
DOI 10.1007/s11104-008-9650-0

REGULAR ARTICLE

Impacts of urea N addition on soil microbial community
in a semi-arid temperate steppe in northern China
Naili Zhang & Shiqiang Wan & Linghao Li & Jie Bi &
Mingming Zhao & Keping Ma

Received: 12 November 2007 / Accepted: 13 May 2008 / Published online: 13 June 2008
# Springer Science + Business Media B.V. 2008

Abstract Nitrogen (N) addition has been well documented to decrease plant biodiversity across various
terrestrial ecosystems. However, such generalizations
about the impacts of N addition on soil microbial
communities are lacking. This study was conducted to
examine the impacts of N addition (urea-N fertilizer)
on soil microbial communities in a semi-arid temperate steppe in northern China. Soil microbial biomass
carbon (C), biomass N (MBN), net N mineralization
and nitrification, and bacterial and fungal community

level physiological profiles (CLPP) along an N
addition gradient (0–64 g N m−2 year−1) were
measured. Three years of N addition caused gradual
or step increases in soil NH4-N, NO3-N, net N
mineralization and nitrification in the early growing
season. The reductions in microbial biomass under
high N addition levels (32 and 64 g N m−2 year−1) are
partly attributed to the deleterious effects of soil pH.
An N optimum between 16 and 32 g N m−2 year−1 in
microbial biomass and functional diversity exists in
Responsible Editor: Lars Jensen.
N. Zhang : S. Wan : L. Li : J. Bi : K. Ma (*)
Key Laboratory of Vegetation and Environmental Change,
Institute of Botany, Chinese Academy of Sciences,
No.20, NanXinCun, Xiangshan,
Beijing 100093, China
e-mail: kpma@ibcas.ac.cn
M. Zhao
College of Life Sciences, Northeast Normal University,
Changchun 130024, China

the temperate steppe in northern China. Similar N
loading thresholds may also occur in other ecosystems, which help to interpret the contrasting observations of microbial responses to N addition.
Keywords CLPP . Microbial biomass . N addition .
Net N mineralization . Nitrification

Introduction
Global nitrogen (N) enrichment resulting from anthropogenic activities can have profound impacts on
the structure and function of terrestrial ecosystems. As
one of the essential components in terrestrial ecosystems, soil microorganisms have been documented to
respond to N enrichment in soils deriving from N
addition or deposition (Fisk and Schmidt 1996;
Michelsen et al. 1999; Stevens et al. 2004; Hines et
al. 2006). In addition, soil microorganisms that have a
high turnover rate can be changed by N addition in a
relatively shorter time in comparison with plant
communities (Bradley et al. 2006). The changes in
soil microbial communities can consequently induce
shifts in soil-based ecosystem processes, i.e., decomposition (Gallo et al. 2004; Liu et al. 2006), carbon
(C) fixation (Frey et al. 2004) and N cycling (Fisk and

Schmidt 1996; Bardgett and Shine 1999; Bardgett et
al. 2002), and then feedback to aboveground plant
communities. Given the important roles of soil
microorganisms in terrestrial ecosystems, a better

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understanding of how soil N enrichment influences
soil microbial communities is essential for explanation of changes in ecosystem structure and function.
Soil microbial community level physiological
profiles (CLPP) via Biolog assay providing a wide
set of compounds can be used to estimate the relative
potential metabolic versatility (Gomez et al. 2006)
and provide further information on the microbial
community responses to N addition. Yet previous
observations call into question whether N addition has
positive or negative effects on soil microbial communities. Variations in the amount of N addition applied
in different experiments may help to explain the
controversial observations. For example, significant
decreases in microbial CLPP under higher N addition

levels (20 and 40 g N m−2 year−1) were observed in a
pasture near Hamilton, New Zealand (Sarathchandra
et al. 2001). However, significant increases in
microbial CLPP under a lower N addition level (4
and 8 g N m−2 year−1) were found in a healthland, and
no change in microbial CLPP was detected at a lower
N addition rate (14 g N m−2 year−1) in a soil-acidic
grassland at Wardlow Hay Cop, Derbyshire (Lee and
Caporn 1998). Therefore, examination of the
responses of soil microbial community along an N
addition gradient in a single ecosystem may help to
find a general pattern of microbial community
response and to explain the contrasting observations
among different studies and ecosystems.
As heterotrophs that depend on plants in acquiring
C substrate, soil microorganisms can be both C- and
N-limited (Gallardo and Schlesinger 1992; Michelsen
et al. 1999). Disproportional supplies of C or N
resources may lead to shift from C-limitation to Nlimitation or vice versa. Low-levels of N addition may
stimulate microbial growth by ameliorating both N

limitation through improving soil N availability and C
limitation via stimulating plant growth and litter
decomposition. However, extra N addition cannot
only lead to C-limitation on microorganisms, but also
result in reduced soil pH (Christie and Beattie 1989;
Malhi et al. 1998). Microbial communities that have
adapted to local habitat are sensitive to changes in soil
pH (Schimel and Weintraub 2003; Wang et al. 2006;
Kemmitt et al. 2006). Decreases in soil pH under
high-level N addition may have a deleterious impact
on soil microbial communities (Soderstrom et al.
1983; Schimel and Weintraub 2003; Kemmitt et al.
2006; Wang et al. 2006). Therefore, we hypothesize

Plant Soil (2008) 311:19–28

that there is a threshold of N addition, at which
microbial responses shift from positive to negative.
The temperate steppe in northern China represents
one of the regional vegetation types of the Eurasian

continent and plays an important role in the national
stock breeding. Most of the local grasslands have
suffered heavily from over-grazing since the early
1980s, resulting in severe land degradation and soil N
deficiency (Christensen et al. 2004; Yuan et al. 2005,
2006). An N addition gradient ranging from 0 to 64 g
N m−2 year−1 has been conducted for 3 years since
2003. The specific objective of this study was to test
the hypothesis proposed in the previous paragraph:
there is a critical N loading level that will trigger
microbial responses along an N addition gradient in
the temperate steppe. Due to close correlation of
growing plants with soil N availability, it is difficult to
distinguish between the direct effects of N addition on
microbial communities and the indirect effects via
altered plant communities. Therefore, we carried out
this study in the early growing season to minimize the
indirect effects of plant growth.

Materials and methods

Site description
The study site was located in Duolun County of
Inner Mongolia, China (42°02′N, 116°16′E,
1,344 m a.s.l.). The climate belongs to the semiarid monsoon climate of the moderate temperate
zone. The long-term mean annual temperature is
2.1°C and the mean annual precipitation is
385 mm. The soil of the study site is sandy soil
classified as chestnut soil according to the Chinese
classification, or Calcic Luvisols according to the
FAO classification with 69.21±0.06% sand, 15.60±
0.02% silt and 15.19±0.02% clay, respectively. The
vegetation is typical steppe dominated by Stipa
krylovii, Artemisia frigida, and Allium bidentatum.
Duolun County in Inner Mongolia is an agropastoral ecotone. Traditional land uses include livestock grazing and farming. From the late 1950s to the
1970s, the government put strict policies into effect to
ban grazing in this region. Since the economic
reforms and open-door policy in 1978, lands were
thrown open to private use. The intensive farming,
grazing and subsequent land-use changes resulted in a

Plant Soil (2008) 311:19–28

smaller area of local grasslands and severe land
degradation (Christensen et al. 2004; Yuan et al.
2005, 2006). Since 2000, new bans on grazing have
been carried out by the local government, but cattle
and sheep grazing are still conducted in some areas of
this region.
Experimental design and soil sampling
The experiment used a Latin square design with sixtyfour 10×15 m plots arranged in eight rows and eight
columns. In early July annually since 2003, each plot
in each row was randomly assigned to one fertilizer
treatment, 0, 1, 2, 4, 8, 16, 32, or 64 g N m−2 year−1
(urea), which were denoted as N0, N1, N2, N4, N8,
N16, N32 and N64, respectively. The distance between
plots was 4 m, and in each plot a buffer zone without
N addition was set up 1 m inside. A simple ANOVA
conducted on soil total N in 2003 showed no
significant differences among different treatment
plots.

Since the plots of the odd rows were clipped on 16
August 2005, soil samples were collected from half of
the 64 plots (i.e., the 32 unclipped plots) with 4
replicates for each treatment (8 N treatments × 4
replicates) at the beginning of the growing season in
May 2006. In order to avoid spatial heterogeneity, 3
cores (4.5 cm in diameter and 15 cm in depth) were
collected along a diagonal line in each plot, and then
completely mixed into one composite fresh sample.
After removal of plant roots and large stones by
sieving (sieve mesh 2 mm), the soil samples were
packed in ice blocks and transported to the laboratory.
Each sample was divided into three sub-samples,
stored at 4°C (for max. 24 h after sampling), −20°C
and air dried, respectively. Three of the four samples
of each treatment stored at 4°C were chosen randomly
to analyze microbial community level physiological
profiles (CLPP). All four soil samples stored at −20°C
were used to determine soil microbial biomass, net N
mineralization and nitrification, while the air-dried

samples were used to determine soil physicochemical
properties.
Soil physicochemical properties and root biomass
A soil water mixture (1:2.5 soil to water ratio) and a
glass electrode (Thermo Orion T20, USA) were used
to determine soil pH. Soil samples were dried for 24 h

21

at 105°C to determine soil moisture. The air-dried
samples, passed through a 0.5-mm sieve, were used to
determine soil organic matter (SOM) and total N
(TN). SOM was measured by the dichromate oxidation and titration method (Kalembasa and Jenkinson
1973), and TN was analyzed using Kjeldahl digestion
method with an Alpkem autoanalyzer (Kjektec System 1026 Distilling Unit, Sweden). Root biomass at
0–15 cm depth was measured by soil auger (7 cm in
diameter).
Microbial properties
Net N mineralization and nitrification were determined by laboratory incubations (Robertson et al.
1999). A flask covered with polyethylene film

(permeable to O2 and CO2 but not to H2O) was filled
with a 10-g soil sample and placed in a humidified,
darkened, 25°C incubator for 28 days. Inorganic N
(NH4+-N and NO3−-N) in initial and incubated
samples were measured by extracting 10 g fresh soil
with 100 ml 2 M KCl for 30 min on a reciprocating
shaker, and then determined by a continuous-flow ion
auto-analyzer (Scalar SANplus segmented flow analyzer, Netherlands). We defined net nitrification as the
difference in NO3−-N before and after the incubation,
and net N mineralization as the difference between
total inorganic N (NH4+-N and NO3−-N) before and
after the incubation.
Microbial biomass carbon (MBC) and nitrogen
(MBN) were determined by using the chloroform
fumigation extraction method (Brookes et al. 1985;
Vance et al. 1987). A 30-g soil composite sample
from each of the 32 samples stored at −20°C was
fumigated with alcohol-free CHCl3 for 24 h after
the samples were pre-incubated in a humidified,
darkened, 25°C incubator for 7 days. Non-fumigated
and fumigated samples were extracted by shaking
them in 100 ml of 0.5 M K2SO4 for 30 min, and then
filtered. Total organic carbon in the extracts was then
measured by potassium dichromate-bitriol oxidation
method (Vance et al. 1987) and total nitrogen in the
extracts by Kjeldahl digestion (Brookes et al.
1985). MBC and MBN were calculated from the
differences between extractable C and N in fumigated and non-fumigated samples using efficiency
factors for microbial C (Kc =0.379; Vance et al.
1987) and microbial N (Kn =0.54; Brookes et al.
1985), respectively.

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Plant Soil (2008) 311:19–28

Soil microbial community level physiological
profiles (CLPP)
Bacterial and fungal CLPP were estimated using
EcoPlates and FF plates, respectively. Further analysis
was performed with the procedure described by Classen
et al. (2003). Soil microbes were extracted from 4 g of
the composite fresh sample with 36 ml of 50 mM
K2HPO4 buffer (pH=6). Soil suspensions were then
shaken for 30 min on a reciprocal shaker. After settling
for 30 min, the soil suspensions were diluted to 10−3
soil solution in sterile inoculating solution consisting of
0.40% NaCl and 0.03% Pluronic F-68 in deionized
water. Fungal extractions were conducted using the
protocols described above except that the inoculating
solution contained streptomycin sulfate (1 µg per
microtiter plate well) and chlortetracycline (0.5 µg
per microtiter plate well) to inhibit bacterial growth.
All solutions, transfer equipments, and glasswares were
sterilized in advance with an autoclave.
Bacterial inoculations were accomplished by transferring 150 μl of solution to each of 96 wells in each
EcoPlate and fungal inoculations using only 100 μl
per well (Buyer et al. 2001; Donbranic and Zak
1999). All plates were placed in polyethylene bags to
reduce desiccation while incubating. EcoPlates were
incubated at 25°C for 96 h and FF plates were incubated
at 25°C for 168 h, and all plates were estimated
once for each 24 h.
Microbial activity expressed as average well-color
development (AWCD) was determined for each
microplate, according to Garland and Mills (1991)
as follows:
AWCD ¼

n
X

ð xi

cÞ=31;

threshold for positive response. Shannon–Wiener
index (H) defining substrate richness and evenness
was calculated as follows:
H¼

n
X

pi ðln pi Þ;

i¼1

where pi is the ratio between the activity of each
substrate and the sum of the activities of all
substrates.
Statistical analyses
The data of soil physicochemical properties, AWCD,
R, and H were analyzed by one-way analysis of
variance (ANOVA) followed by Turkey’s HSD test
with SAS 9.0. The multivariate data from CLPP were
assessed by canonical correspondence analysis (CCA)
with vegan package of R, which supports all basic
ordination methods and functions for both fitting
environmental variables and ordination graphics.

Results
Physicochemical properties
Soil NO3−-N increased gradually with the amount of N
addition, whereas soil NH4+-N concentrations showed
a step increase at the highest rate of 64 g N m−2 year−1
(Table 1). The significant decreases in soil pH (P<
0.05) at high N addition rates (N32 and N64) were
observed.
Microbial biomass and activities

i¼1

where xi is the optical density value measured at
595 nm or 750 nm in substrate i in EcoPlates or
FF plates respectively, and c is the value measured
in the control well. The pattern of substrate
utilization of each plate was expressed using
transformed data calculated by dividing the raw
difference value for each well by the AWCD of
P
the plate: ðxi cÞ= ðxi cÞ=31, and transformed
values of > 1 indicate that color responses are
positive (Garland and Mills 1991). Richness (R), as
the number of oxidized carbon resources, was
calculated using a transformed value of > 1 as the

After 3 years of N addition, there was substantial
variability in soil microbial biomass C across the
8 treatments with the greatest MBC under the N16
treatment, which was significantly higher than those
under the N2 and N64 treatments. Soil microbial
biomass N slightly increased at the two low levels of
N addition (N1 and N2), but decreased with the
addition of more N fertilizer, especially under the two
highest N addition levels (Table 1). Across the 32
sampled plots, MBC positively depended on SOM
(r2 =0.85, p