Journal Pre-proof Influences of nitrogen addition and aboveground litter-input manipulations on soil respiration and biochemical properties in a subtropical forest Yong PENG, Si-yi SONG, Zeng-yan LI, Shun LI, Guan-tao CHEN, Hong-ling HU, Jiulong XIE, Gang CHEN, Yin-long XIAO, Li LIU, Yi TANG, Li-hua TU PII:
S0038-0717(19)30358-X
DOI:
https://doi.org/10.1016/j.soilbio.2019.107694
Reference:
SBB 107694
To appear in:
Soil Biology and Biochemistry
Received Date: 4 August 2019 Revised Date:
7 December 2019
Accepted Date: 8 December 2019
Please cite this article as: PENG, Y., SONG, S.-y., LI, Z.-y., LI, S., CHEN, G.-t., HU, H.-l., XIE, J.-l., CHEN, G., XIAO, Y.-l., LIU, L., TANG, Y., TU, L.-h., Influences of nitrogen addition and aboveground litter-input manipulations on soil respiration and biochemical properties in a subtropical forest, Soil Biology and Biochemistry, https://doi.org/10.1016/j.soilbio.2019.107694. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Elsevier Ltd. All rights reserved.
1
Influences of nitrogen addition and aboveground litter-input manipulations on soil respiration
2
and biochemical properties in a subtropical forest
3 4 5 6
Figure 1 Location of study site in Ya’an, Sichuan province, China and the schematic design of N addition and aboveground litter manipulation.
1
CN LN HN
Cumulative litterfall (t ha-1)
200 Time effect (P < 0.001) Nitrogen effect (P = 0.921) Time x Nitrogen effect (P = 0.438)
150
15 CN LN HN
10 5
2015
2016
Jun.-17
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Litterfall (g m )
0 2017
Total
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0
Figure 2 Seasonal variations in above-ground litter input in an evergreen broad-leaved forest in southwestern China from August 2015 to December 2017.
2
0
11 12 13 Jun.-17 Jul.-17 Aug.-17 Sep.-17 Oct.-17 Nov.17 Dec.17
Jun.-17 Jul.-17 Aug.-17 Sep.-17 Oct.-17 Nov.17 Dec.17
20 May-17
40
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60 Apr.17
CN LN HN
Apr.17
(B)
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Feb.-17
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80
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Jul.-16
Jun.-16
May-16
Apr.16
100
Mar.-16
Feb.-16
4 Jan.-16
o
Soil temperature ( C) 22
Jan.-16
Soil moisture content (%)
10 24 (A) CNLLNLHNLCNL0 LNL0 HNL0 CNL+ LNL+ HNL+
10
8
6
Figure 3 Seasonal variations in soil temperature (A) and soil moisture content (B) in an evergreen
broad-leaved forest in southwestern China from January 2016 to December 2017.
3
0
16 17 18 Feb.-16
Dec.17
Nov.17
Oct.-17
Sep.-17
Aug.-17
Jul.-17
Jun.-17
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Sep.-16
Aug.-16
Jul.-16
Jun.-16
3
May-16
4
Apr.16
5
Mar.-16
15 Jan.-16
-2 -1
Soil CO2 efflux (µmol CO2 m s )
14 6
CNLLNLHNLCNL0 LNL0 HNL0 CNL+ LNL+ HNL+
2
1
Figure 4 Seasonal variations in soil respiration in an evergreen broad-leaved forest in
southwestern China from January 2016 to December 2017.
4
-1 Cumulative C flux (t C ha )
25 a
CNLLNLHNLCNL0 LNL0 HNL0 CNL+ LNL+ HNL+
20
15
10
ab bc bcd
d
e
cd
ab bc a
bc
bc ab
bc cde
bcd
a
ab b
bcd cd
c
c
bc
c
bcd
de
5
0
19 20 21
2016
2017
Total
Figure 5 Cumulative CO2 flux under different treatments.
5
Soil CO2 efflux (µmol CO2 m-2 s-1)
CNLLNLHNLCNL0 LNL0 HNL0 CNL+ LNL+ HNL+
(A)
6
4
(B)
y = 0.562 e 0.095x P < 0.001 R2 = 0.759
4
2
2
0
0 4
22 23
y = 0.653 x 0.223 P < 0.001 R2 = 0.149
6
6
8
10 12 14 16 o Soil temperature ( C)
18
20
0
200
400 600 -2 Litter input (g m )
800
Figure 6 Relationships between soil respiration and soil temperature (A) and litterfall (B).
6
Highlights •
The aboveground litter-input was added or reduced by only 50%
•
Nitrogen addition increased the topsoil TOC concentration when no litter changed
•
The increase of soil C content may be due to the inhabitation of SOM decomposition
•
Litterfall alteration reduced topsoil TOC concentration when N input increased
1
Influences of nitrogen addition and aboveground litter-input manipulations on soil respiration
2
and biochemical properties in a subtropical forest
3
Yong PENGa, b, Si-yi SONGa, Zeng-yan LIa, Shun LIc, Guan-tao CHENd, Hong-ling HUa, Jiu-long
4
XIEa, Gang CHENa, Yin-long XIAOe, Li LIUf, Yi TANGg, Li-hua TUa,*
5 6
a
Key Laboratory of National Forestry & Grassland Administration on Forest Resources Conservation
7
and Ecological Safety in the Upper Reaches of the Yangtze River, College of Forestry, Sichuan
8
Agricultural University, Chengdu, Sichuan, 611130, China
9
b
The University of Tokyo Hokkaido Forest, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Furano, Hokkaido, 079-1564, Japan
10 11
c
Sichuan Academy of Forestry, Chengdu, Sichuan, 610084, China
12
d
Soil Science of Tropical and Subtropical Ecosystems, Faculty of Forest Sciences and Forest Ecology, University of Goettingen, Goettingen, 37077, Germany
13 14
e
College of Environmental Sciences, Sichuan Agricultural University, Chengdu, Sichuan, 611130, China
15 16
f
Personnel Department, Sichuan Agricultural University, Chengdu, Sichuan, 611130, China
17
g
College of Horticulture, Sichuan Agricultural University, Chengdu, Sichuan, 611130, China.
18
*
Corresponding author: College of Forestry, Sichuan Agricultural University, No. 211 Huimin Road,
19
Wenjiang District, Chengdu, Sichuan, 611130, China.
20
E-mail address:
[email protected]
21
Yong PENG, Si-yi SONG, Zeng-yan LI, and Shun LI contributed equally to this work.
22 23 24 1
25
Abstract:
26
Atmospheric nitrogen (N) deposition has rapidly increased in subtropical ecosystems and may have
27
altered the input of aboveground litter to soil, which substantially impacts soil carbon (C) and nutrient
28
cycling. But how the soil processes and properties respond to N deposition under uncertain fresh litter
29
input is poorly understood. In order to examine the responses of soil respiration and biochemical
30
properties to N addition and aboveground litter manipulation, a field N addition and litterfall
31
manipulation interaction experiment was performed in an evergreen broadleaf forest on the western
32
edge of the Sichuan Basin in China. Three levels of N addition, including an N control (CN, ambient N
33
input) and low N (LN, + 50 kg N ha
34
levels of litterfall manipulation, including intact litter input (L0, no litter alteration), litter reduction (L−,
35
reduced by 50%) and litter addition (L+, increased by 50%), were conducted monthly starting in
36
January 2014 and August 2015, respectively. Soil respiration was measured monthly from January
37
2016 to December 2017. Soil samples were collected four times, in October 2016 and January, April
38
and July 2017, to measure soil biochemical properties. The results showed that: (1) short-term N
39
addition did not significantly alter the aboveground litter input in this forest; (2) soil respiration
40
decreased with elevating N input and was associated with amount of litterfall input; (3) N addition
41
increased the total organic C (TOC) concentration in topsoil in subplots without litterfall alteration but
42
did not affect TOC in subplots with increased or decreased litter-input; (4) N addition decreased soil
43
pH and did not affect soil microbial biomass regardless of whether litterfall was altered or not; (5)
44
short-term litter manipulation did not affect any soil properties in the N control plots, but both litterfall
45
reduction and addition tended to reduce surface soil TOC concentration in the N-added plots; and (6)
46
both N addition and litterfall manipulation showed stronger effects on organic soil than on mineral soil.
47
These findings indicated that elevated N input increased the surface soil C content by reducing soil
48
respiration mainly via enhancing stabilization of soil organic matter rather than by reducing soil
49
microbial biomass, and that altered litterfall may mitigate the N-induced increase in soil C. Because of
50
temporal lag, long-term experimentation is needed to investigate the response of soil to altered litter
51
input under different N addition conditions.
52
Key words: Nitrogen addition; litter manipulation; soil respiration; soil carbon
−1
−1
year ) and high N (HN, + 150 kg N ha
−1
−1
year ), and three
53
2
54
Introduction
55
Over the past few decades, anthropogenic reactive nitrogen (N) inputs have substantially increased
56
and exceeded the N inputs through all-natural processes due to the application of N fertilizer and the
57
burning of fossil fuels (Davidson, 2009). Increased N deposition has been one of the major contributors
58
to global change and has altered terrestrial vegetation biomass (Devaraju et al., 2016; Yue et al., 2017)
59
and the input amount of aboveground litter to soil (Li et al., 2010a; Field et al., 2017). Soil, as the
60
largest carbon (C) pool in the terrestrial ecosystem, stores more organic C than vegetation and the
61
atmosphere and plays an important role in global and regional C and nutrient cycling as well as in C
62
feedback to global environmental changes (Schmidt et al., 2011; Lehmann and Kleber, 2015). Soil C
63
dynamics depend on the balance between C input and output and are regulated by many biotic and
64
abiotic factors, such as plant inputs, N availability, microbial transformations and stabilization of soil
65
organic matter (SOM) (Paul, 2016). Therefore, changes in N and aboveground litter inputs may affect
66
soil C dynamics, and the response of soil C dynamics to N addition and aboveground litter
67
manipulation may have considerable impacts on CO2 exchange between the biosphere and atmosphere.
68
Considerable attention has been devoted to the responses of soil C dynamics with elevated N inputs
69
to soil. Because ecosystem C dynamics are tightly coupled to N cycling (Ye et al., 2018; Wang et al.,
70
2019), the remarkable increases in atmospheric N deposition have considerably influenced processes of
71
natural ecosystems, such as plant productivity (Yan et al., 2014; Devaraju et al., 2016), litterfall (Li et
72
al., 2010a; Field et al., 2017) and litter decomposition (Whalen et al., 2018; Zhang et al., 2018), which
73
in turn impact soil C dynamics (Ye et al., 2018; Wang et al., 2019). Globally, anthropogenic N input has
74
led to an increase in soil C storage (Frey et al., 2014; Devaraju et al., 2016; Wang et al., 2017). With N
75
limiting in most terrestrial ecosystems (LeBauer and Treseder, 2008), N enrichment can generally
76
promote vegetation biomass (Yan et al., 2014; Devaraju et al., 2016; Wang et al., 2017) and thus
77
increase the C input to soil. In addition, elevated N inputs can reduce soil CO2 emission in many
78
ecosystems by reducing SOM decomposition rates (Bowden et al., 2004; Janssens et al., 2010; Fan et
79
al., 2014; Peng et al., 2018; Zhou et al., 2018; Wang et al., 2018). However, a neutral or negative effect
80
of N addition on soil C dynamics was also observed in some ecosystems (Lu et al., 2011; Reid et al.,
81
2012; Forstner et al., 2018). For instance, Forstner et al. (2018) reported that enhanced N input
82
decreased SOC pools in the mineral topsoil in two temperate coniferous forests, which probably 3
83
resulted from decreased belowground C input and/or increased C output due to accelerated
84
decomposition.
85
Plant litter is an inherent part of C and nutrient cycling and also a buffer or protective layer on the
86
surface soil of soil C, and variation in litter input can thus affect the soil C dynamics directly and
87
indirectly (Sayer, 2005). A great number of litter manipulation experiments have been conducted to test
88
the effect of alterations in litter input on belowground C dynamics (Sayer et al., 2011; Leff et al., 2012;
89
Lajtha et al., 2014a, 2014b, 2018; Han et al., 2015; Pisani et al., 2016; Wu et al., 2017; Cusack et al.,
90
2018). Numerous studies demonstrated that soil respiration, microbial biomass, and soil C content are
91
associated with the amount of litterfall (Xu et al., 2013a; Lajtha et al., 2014a; Chen and Chen, 2018;
92
Cusack et al., 2018). Generally, litter exclusion leads to reduced surface soil C storage due to a direct
93
reduction in the input of C to soil (Bowden et al., 2014; Lajtha et al., 2014a, 2014b, 2018; Cusack et al.,
94
2018). However, the addition of litter does not always lead to increased soil C content. In many
95
ecosystems, litter addition does not affect or even reduces soil C content (Bowden et al., 2014; Pisani et
96
al., 2016; Lajtha et al., 2014b, 2018). The neutral or negative effect has been considered due to the
97
accelerated native SOM degradation caused by increased litter input, i.e., a priming effect (Kuzyakov et
98
al., 2000; Bowden et al., 2014; Lajtha et al., 2018). It is noteworthy that aboveground litters were either
99
completely excluded or doubled in most litter manipulation experiments (Sayer et al., 2011; Bowden et
100
al., 2014; Pisani et al., 2016; Gao et al., 2018; Cusack et al., 2018; Rodtassana and Tanner, 2018).
101
However, complete removal or doubling of litterfall can only explore the role of litter in an ecosystem
102
and cannot properly simulate the impact of an increase or decrease of litterfall with changes in net
103
primary productivity (NPP) on belowground physicochemical and biological processes. First, the
104
magnitude of alteration of litterfall due to the global change in natural ecosystems is much smaller than
105
100%. For instance, the increase in litterfall induced by increased N input to date is less than 20%
106
across all terrestrial ecosystems and is only ~10% on average in forest ecosystems (Liu and Greaver,
107
2010; Yue et al., 2016). Magill et al. (2004) reported that long-term N application in an N-saturated
108
forest led to forest decline, thereby reducing litterfall. Predictably, this reduction of litter input is
109
unlikely to reach 100% and shows little effect on the fauna and microflora in the original litter layer. In
110
addition, the removal of aboveground litter completely removes the animal and microbial communities
111
in the original litter layer and also impacts the temperature and moisture of the soil surface (Sayer,
112
2005; Xu et al., 2013a). Therefore, complete removal of litter is not suitable for simulating the litter 4
113
reduction scenario. To be more in line with natural conditions, the original litter layer should be present
114
during a litterfall manipulation experiment. However, to our knowledge, no such study has been
115
published to date. Klotzbücher et al. (2012) looked like did a similar experiment in which the effect of
116
80% litter input alteration on dissolved organic matter was studied in a Norway spruce (Picea abies)
117
stand, but they also completely removed or doubled the aboveground litter input during the snow-free
118
period (approximately 80% of the year) and did not conduct any litter manipulations during
119
winter-time.
120
Here, the effects of alteration in aboveground litter input on the belowground physicochemical and
121
biological processes were investigated by periodically increasing or decreasing 50% of recent litterfall
122
without changing the original litter layer.
123
The Rainy Zone of Western China, which is a large and complex ecotone on the western edge of the
124
Sichuan Basin, ranges 400–450 km from north to south and 50–70 km from east to west, with an area
125
of approximately 25,000 km2 (Zhuang and Gao, 2002). This region is located in a mid-subtropical
126
evergreen broad-leaved forest zone with a humid and monsoon-influenced climate and is an important
127
habitat for the giant panda (Ailuropoda melanoleuca). Due to the influence of the steep terrain on the
128
eastern side of the Tibetan Plateau and the monsoon climate, warm moist air from the Sichuan Basin
129
readily reaches supersaturation and forms abundant rainfall on the western edge of the basin (Zhuang
130
and Gao, 2002; Li et al., 2010b), and thus, atmospheric N deposition in this area is mainly via wet
131
deposition (Yang et al., 2018). The mean annual atmospheric N wet deposition in the center of this
132
zone (Ya’an city) was approximately 95 kg N ha−1 (Xu et al., 2013b), which is much greater than the
133
average level of China (21.1 kg N ha−1) (Liu et al., 2013). Previous N addition experiments conducted
134
in this area demonstrated that elevated N input lessened the soil C emission of two natural evergreen
135
broadleaf forests by reducing fine root biomass, soil microbial biomass and litter decomposition (Zhou
136
et al., 2017, 2018; Peng et al., 2017, 2018). This negative response of soil C efflux might increase soil
137
C sequestration in these evergreen broad-leaved forests. However, the responses of aboveground plant
138
input to N addition and of soil biochemical processes to altered litterfall under different N-addition
139
conditions remain unclear.
140
Thus, we performed a field N addition and aboveground litter manipulation experiment in a
141
subtropical evergreen broadleaf forest in the Rainy Zone of Western China to investigate the response
142
of soil biochemical properties to N addition and/or aboveground litter alteration. We hypothesized that: 5
143
(1) N addition would enhance soil C content by reducing soil respiration; (2) litterfall reduction would
144
decrease the soil respiration rate because of reduced substrate, while litterfall addition would stimulate
145
soil CO2 emission due to enhanced substrate availability and by a priming effect; and (3) a combination
146
of N and litterfall addition would lead to a minor change in soil respiration, while combined N addition
147
and litterfall reduction would cause further reduction of soil respiration.
148
Materials and methods
149
Site description
150
The field experiment was conducted in an evergreen broadleaf secondary forest in Bifeng Valley
151
Ecological Scenic Area (30º 04′ N, 103º 00′ E, 1,030 m a.s.l.), a national park in Ya’an, Sichuan
152
Province, China (Fig. 1 A, B), which is located in the centre of the Rainy Zone of Western China. The
153
annual average precipitation and temperature are 1750 mm (with 215 annual rainy days, Li et al.,
154
2010b) and 13.9 ºC, respectively. The soil in this study site is classified as a Ferralsol (according to
155
World Reference Base for Soil Resources 2014), with old alluvial yellow loam, with a granular
156
structure, > 60 cm depth. The dark humus layer of the soil here is loam, around 10 cm thick, with little
157
stones. The soil beneath the humus layer is a yellow iron-aluminum accumulation layer of about 50 cm,
158
with a strong viscosity. The nature of bedrock is granite. The litter stock in this forest was 20.6 ± 3.4 t
159
ha . The forest canopy mainly included Castanopsis fargesii, Schima superba, Symplocos botryantha,
160
S. setchuensis, Quercus fabri and Cunninghamia lanceolata, with average tree density and
161
breast-height diameter of 1,631 ± 130 stems ha
162
were primarily Daphniphyllum macropodum, Toxicodendron succedaneum, and Smilax china.
163
Common herbs included Murdannia triquetra, Sarcopyramis bodinieri and ferns.
164
Experimental design
−1
−1
and 11.6 ± 0.7 cm, respectively. The understory trees
165
In November 2013, twelve 20 m × 20 m experimental plots were established as a randomized block
166
design, at intervals of > 20 m (Fig. 1 C). These plots were randomly divided into three N addition
167
treatments, i.e., control N treatment (CN, ambient N deposition), low N (LN, + 50 kg N ha
168
and high N (HN, + 150 kg N ha
169
treatments, LN and HN, were applied to simulate scenarios of N wet deposition roughly increased by
170
50% and 150% in this region, respectively. Nitrogen was added in the form of ammonium nitrate
−1
−1
−1
year )
−1
year ), with four replicates for each treatment. The two N addition
6
171
(NH4NO3) to simulate increased N deposition because atmospheric N deposition is mainly composed
172
of ammonium (NH4 ) and nitrate (NO3 ). NH4NO3 dissolved in 10 L water was added to the soil
173
surface monthly using a backpack sprayer starting in January 2014. Control plots received 10 L of
174
water without NH4NO3. The amount of external water added to each plot when N is applied every year
175
is only equivalent to an increase of 0.3 mm (0.017%) annual precipitation. Thus, the influence of
176
additional water can be ignored.
177
+
At the end of July 2015, nine 2 m
−
× 2 m subplots were randomly established in each N treatment
178
plot and divided into three litter treatments with tree replicated for each treatment (Fig. 1 D): litter
179
reduction (L−, reduced by 50%), litter addition (L+, increased by 50%), and intact litter input (L0, no
180
litter alteration). For the L− treatment, a 2 m × 2 m nylon mesh (size is 1 mm) litter trap was set above
181
each L− subplot to prevent fresh litter input at the end of July 2015 (Fig. 1 E). Beginning in August
182
2015, the litter materials in each litter trap were weighed and recorded on-site monthly and divided into
183
two portions; then, one portion was evenly added to the L− subplot, and the other portion was added to
184
an adjacent L+ subplot. For the L0 subplot, the natural aboveground litter input was maintained. In
185
addition, to calculate the litter water content, litter materials of each plot were collected from a 0.5 m ×
186
0.5 m litter trap which was randomly set in each N treatment plot and brought back to the laboratory.
187
Litter manipulation occurred before N application in every month.
188
Soil respiration measurement
189
In December 2015, a PVC soil respiration (RS) sampling collar (20 cm inside diameter and 8 cm
190
height) was inserted in each subplot for RS measurement. PVC collars were inserted into the soil
191
surface at approximately 6 cm depth and left in situ throughout the study period. A Li-8100 automated
192
soil CO2 efflux system (LI-COR Inc., Lincoln, NE, USA) was used to measure RS once monthly from
193
January 2016 to December 2017. All RS measurements included both litter layers and mineral soil and
194
occurred between 10:00 am and 15:00 pm (local time) on a rainless day before litter manipulation and
195
N addition (Peng et al., 2018). Our previous measurements showed that the soil CO2 fluxes measured
196
within same period approximately equal to the average soil respiration rates of the diel cycle. The
197
average RS rate of three subplots under same treatment in a plot was assumed to represent the diurnal
198
mean of the treatment in the plot, and the total quantity of CO2 emission on that day was multiplied by
199
the number of days of the sampling month to estimate the total CO2 emission of that month (Fan et al., 7
−2
−1
−1
200
2014). The rates of RS and CO2 emission were expressed as µmol CO2 m
201
respectively. The soil temperature at 10 cm below the soil surface was measured for each subplot with
202
a temperature probe at the same time when RS was measured, while the soil moisture content in the
203
upper 5 cm of the soil horizon was measured only for L0 subplots (i.e., soil moisture contents in L−
204
and L+ subplots were not measured) by the gravimetric method with oven drying (dried at 105 °C for
205
24 h).
206
Soil sampling
s
and t C ha ,
207
Soil samples were collected four times: in October 2016 and in January, April and July 2017.
208
Because both N addition and litter manipulation occurred at the surface of the soil and were carried out
209
for only 3-4 years and 1-2 years, respectively, which is unlikely to impact deep soil, thus we only
210
sampled the first 20 cm soil. At each time, within each subplot, the plant litter was removed, and a soil
211
core of the top 20 cm soil horizon was randomly obtained using a soil auger and divided into the
212
organic horizon (including the O and A horizons, with dark color and thickness of approximately 10 cm)
213
and mineral layer (the soil beneath the organic horizon, with thickness of approximately 10 cm) based
214
on soil color. Soil cores of the same soil layer from three subplots under the same litter treatment were
215
mixed as a soil sample. Therefore, there were three different soil samples collected from each N
216
treatment plot for each soil layer, and in total, thirty-six soil samples for each soil layer were obtained
217
for each sampling time.
218
Soil chemistry analysis
219
Fresh soil samples were brought back to the laboratory and immediately ground and sieved through a
220
2-mm mesh after carefully removing the visible roots using tweezers. Then, these samples were divided
221
into two parts. One part was stored at 4 ºC for measuring ammonium (NH4 ), nitrate (NO3 ), microbial
222
biomass carbon (MBC), microbial biomass nitrogen (MBN) and extractable dissolved organic carbon
223
(EDOC) within one week; the other part was air-dried and used for measuring total organic carbon
224
(TOC), readily oxidizable carbon (ROC) and total nitrogen (TN) after being ground and sieved through
225
a 0.25-mm mesh and for measuring soil pH after being ground and sieved at 2 mm.
+
+
−
−
226
Soil NH4 and NO3 were extracted by a 2 M KCl solution (Maynard et al., 2007), and measured
227
with a colorimetric method based on the color reaction between NH4 and a weakly alkaline mixture of
228
Na salicylate and a chlorine source in the presence of Na nitroprusside (Baethgen and Alley, 1989) and
+
8
229
a two-wavelength ultraviolet spectrum approach (Edwards et al., 2001), respectively. The soil MBC
230
and MBN were measured with the 24-h chloroform fumigation extraction technique (Wu et al., 1990;
231
Brookes et al., 1985) and a total C/N analyzer (Shimadzu model TOC-VcPH +TNM-1, Kyoto, Japan).
232
Soil MBC and MBN were calculated as the differences in 0.5 M K2SO4-extractable C or N between
233
fumigated and unfumigated soils, which were divided by 0.45 (Wu et al., 1990) and 0.54 (Brookes et
234
al., 1985), respectively. The K2SO4-extractable C in unfumigated soils was calculated as EDOC. Soil
235
TOC and ROC were measured by the dichromate digestion method (Soon and Abboud, 1991) and
236
KMnO4 oxidation method (Blair et al., 1995), respectively. The soil TN concentration was determined
237
by the Kjeldahl method (Rutherford et al., 2007). Soil pH was determined using a glass electrode in
238
aqueous extracts with a ratio of 1:2.5 (w/v).
239
Statistical analysis
240
Average values of all parameters from each plot under the same treatment from each sampling date
241
were used for data analysis. All parameters were first tested for normal distribution and homogeneity of
242
variances using Shapiro-Wilk’s test and Levene’s test, respectively. Parameters with nonnormal or
243
unequal variances were transformed using the Box-Cox method. One-way repeated-measures analysis
244
of variance (ANOVA) with a post hoc LSD test was used to detect the effects of N addition
245
(between-subjects factor), sampling time (within-subjects factor), and their interaction on litter input.
246
One-way ANOVA with a post hoc LSD test was used to determine the effect of N addition on litterfall
247
for 2015, 2016, 2017 and the whole study period, separately. Two-way repeated-measures ANOVA
248
with a post hoc LSD test was used to determine the effects of N addition and litter manipulation (two
249
between-subjects factors), sampling time (within-subjects factor), and their interactions on RS, soil
250
temperature, soil moisture and soil properties (TOC, ROC, EDOC, TN, NH4+, NO3−, MBC, MBN, C/N
251
and pH). For RS, separate analyses were conducted for 2016, 2017 and whole study period. For soil
252
biochemical characteristics, analyses were conducted for each soil layer separately. Two-way ANOVA
253
was used to detect the effects of N addition and litter manipulation on soil cumulative CO2 efflux for
254
2016, 2017 and whole study period. Nonlinear regression was used to determine the correlations
255
between RS rates and soil temperature, litter inputs or soil moisture. All the above analyses were
256
conducted using IBM SPSS statistics 20.0 for Windows (IBM Crop., Armonk, New York, USA), and
257
statistically significant differences were determined at P < 0.05. 9
258
Results
259
Aboveground litter input
260
Aboveground litter input in this forest displayed significant variation throughout the research period
261
(Fig. 2). The annual mass of litterfall was 5.7 ± 0.7 t ha−1 and 4.5 ± 0.5 t ha−1 in 2016 and 2017,
262
respectively. Generally, there were two litter input peaks (May to July and October to December) each
263
year. The proportion of litterfall in these months reached 66%. The lowest litterfall was observed in
264
January, only 1% of the annual amount. According to the repeated measures ANOVA, N additions did
265
not alter the aboveground litter input. In the whole study period (August 2015 to December 2017), the
266
total amount of added or reduced litterfall in L+ or L− subplots was 6.5 t ha−1.
267
Soil temperature and moisture
268
In this forest, soil temperature varied greatly throughout the study period (Fig. 3A). The annual
269
average temperature was 12.9 °C, with the highest value (19.6 °C) in August and the lowest value
270
(6.1 °C) in January. However, the soil water content remained relatively stable over the study period,
271
ranging from 43.1% to 67.6% (Fig. 3B). The annual mean soil moisture content was 56.2% and 55.1%
272
in 2016 and 2017, respectively. Repeated measures ANOVA showed that neither N addition nor
273
litterfall alteration significantly affected the soil temperature; there was also no significant N effect
274
observed on the soil water content (Table 1). Because the soil moisture contents in the L− and L+
275
subplots were not measured, the influence of litter input manipulation on soil moisture was not
276
analyzed.
277
Soil respiration and microbial biomass
278
Similar to soil temperature, soil respiration showed significant seasonal dynamics, with the lowest
279
value (1.07 µmol CO2 m−2 s−1) in January and the highest value (4.58 µmol CO2 m−2 s−1) in July (Fig. 4).
280
Annual cumulative CO2 fluxes in this forest were 8.2 and 11.3 t C ha−1 yr−1 in 2016 and 2017,
281
respectively (Fig. 5). The seasonality of soil respiration was mainly explained by soil temperature and
282
aboveground litter input. In this forest, soil respiration was significantly positively exponentially
283
related to soil temperature (P < 0.001, R2 = 0.759; Fig. 6 A) and positively related to litterfall via a
284
power function (P < 0.001, R2 = 0.149; Fig. 6 B). However, the correlation between soil respiration and
285
soil moisture was insignificant because soil moisture content varied slightly across the study period. 10
286
Two-way repeated-measures ANOVA revealed that both N addition and litter input alteration
287
significantly altered soil respiration (N effect, P < 0.001; litter effect, P = 0.003), but no significant
288
interactive effects among sampling time, N addition and litter alteration were observed (Table 2).
289
Nitrogen addition significantly reduced soil respiration in subplots with intact litter input in the whole
290
study period by 14.8%−29.3% (P = 0.006; Fig. 5) but insignificantly in subplots with litter reduction or
291
addition (P = 0.161 and P = 0.082, respectively; Fig. 5). Soil CO2 efflux significantly increased with
292
increasing aboveground litter input. The combined L− and N addition treatments significantly (P <
293
0.05) decreased soil respiration and showed a stronger effect than L− or N addition alone; however, the
294
combination of L+ and N addition did not affect soil CO2 efflux. Litter reduction and addition likely
295
promoted and alleviated the negative effect of N addition on soil CO2 emission, respectively.
296
The soil MBC and MBN in the organic horizon and mineral horizon varied significantly in different
297
seasons (P < 0.001; Table 3). The soil MBC and MBN in the organic horizon were greater than those
298
in the mineral horizon (P < 0.001). Added N did not change the soil MBC and MBN in both layers
299
except for a marginally decreased MBN of the organic horizon by 16%−24% (P = 0.053). Litter input
300
alteration did not affect the soil MBC and MBN in both layers. No significant interactive effects among
301
sampling time, N addition and litter manipulation on the soil MBC and MBN were observed.
302
Soil carbon
303
The soil TOC in the organic horizon and ROC and EDOC in both layers displayed significant
304
seasonal variations (P < 0.001; Table 3). The soil TOC and ROC concentrations in the organic horizon
305
were much higher than those in the mineral horizon (P < 0.001). However, there was no significant
306
difference in soil EDOC concentrations between the two soil layers. Two-way repeated-measures
307
ANOVA revealed that both N addition and litterfall manipulations significantly affected soil TOC
308
concentrations in the organic soil layer (P < 0.01). Nitrogen addition increased the soil TOC
309
concentration in the organic soil layer in the litter control subplots but not in the subplots with litter
310
reduction or addition. In the N-added subplots, both L– and L+ decreased soil TOC concentration in
311
organic soil, but no significant effect was found in N controls. Nitrogen addition was associated with a
312
significant increase in soil ROC concentration in the organic horizon (P = 0.008). The soil ROC
313
concentration in the organic soil in subplots without litterfall alteration significantly increased with N
314
addition but did not change in the subplots with litterfall reduction or addition. However, litterfall 11
315
alteration was not associated with soil ROC in the organic soil layer. Neither N addition nor litterfall
316
manipulation influenced TOC and ROC in the mineral soil layer or EDOC in both soil layers. There
317
were no interactive effects among sampling time, N addition and/or litter manipulation observed.
318
Soil nitrogen
319
The soil TN, NO3− and NH4+ concentrations in both the organic horizon and mineral horizon varied
320
significantly throughout the study period (P < 0.001; Table 3). Neither N addition nor litter input
321
manipulation altered soil TN in both soil layers. Nitrogen addition significantly increased the average
322
NO3− concentrations in the organic horizon and mineral horizon by 28.6%−68.9% and 18.5%−103.8%
323
and increased the average NH4+ concentrations by 37.6%−217.9% and 10.0%−108.1%, respectively (P
324
< 0.001). Nitrogen addition showed a significant interactive effect with sampling time on NO3−
325
concentrations in the organic horizon and NH4+ concentrations in both soil layers (P < 0.001). The
326
positive responses of soil NO3− and NH4+ concentrations to N addition were observed in all
327
litter-manipulation treatments and both soil layers (P < 0.005). Combined with N addition, L−
328
significantly increased NH4+ concentrations in the organic horizon (P < 0.05) but did not affect the
329
NH4+ concentration in mineral soil or NO3− concentrations in both soil layers. There was also no
330
interactive effect between N addition and litter manipulation on soil TN, NO3−, and NH4+
331
concentrations.
332
Soil C: N ratio and pH
333
The soil C:N ratio varied significantly throughout the study period (P < 0.003, Table 3). In the
334
organic horizon, N addition significantly increased the soil C:N ratio (P = 0.004). Both L− and L+
335
tended to reduce the soil C:N ratio in the organic horizon, which reached a significant level when
336
combined with LN treatment (P < 0.05). Neither N treatments nor litter manipulations affected the soil
337
C:N ratio in the mineral horizon. There was no interactive effect between N addition and litter input
338
alteration on the soil C:N ratio.
339
The soil pH varied significantly throughout the study period (P < 0.001, Table 3). Nitrogen addition
340
was associated with a significant decrease in soil pH in both soil layers (P < 0.001). Litter manipulation
341
did not change soil pH in either layer. There was no interactive effect between N addition and litter
342
input alteration on soil pH.
12
343
Discussion
344
Effect of nitrogen additions on aboveground litter input
345
As the major pathway to return C and nutrients to the soil from vegetation, litterfall reflects the net
346
primary productivity of forest ecosystems (Malhi et al., 2011). Because most forest ecosystems are
347
N-limited (LeBauer and Treseder, 2008), N addition is believed to potentially alleviate this limitation,
348
thereby promoting net primary productivity (NPP) (Law, 2013; Yan et al., 2014) and, in turn, increasing
349
the amount of aboveground litter (Magill et al., 2000; Li et al., 2010a; Field et al., 2017). By
350
synthesizing studies in 32 forest ecosystems around the world, Yue et al. (2016) reported that global
351
forest litterfall increased by an average of 10.8% with the recorded increase of N input and that the
352
effects of high N addition levels were more pronounced compared with the effects of low N addition
353
levels. However, our results showed that 3−4 years of N application had no significant influence on
354
litterfall, consistent with some previous studies (Mo et al., 2008; Cusack et al., 2011; Peng et al., 2017),
355
probably because 3-4 years of N addition do not supply an extra input of N enough to result in
356
significant increases in plant production. This pattern may occur because this forest is N-rich, as the
357
atmospheric N-deposition rate in this region is very high (95 kg N ha−1 yr−1, Xu et al. 2013b) and thus
358
led to a high N concentration (41.9 g kg−1 and 9.5 g kg−1 for the organic and mineral horizon,
359
respectively) in soil in this forest. Similarly, the N concentrations in soils in the above-cited studies
360
(Mo et al., 2008; Cusack et al., 2011; Peng et al., 2017) are also very high. Therefore, the possibility
361
that these forests have become N-saturated may be another reason why N addition did not affect
362
litterfall. Lu et al. (2018) reported that even 10 years of N addition did not significantly alter litterfall
363
production in an N-rich tropical forest. However, in a temperate forest, litterfall response to N addition
364
changed from increasing early in the chronic N addition to decreasing over time when the soil became
365
N-saturated (Magill et al. 2004). It is likely that the direction and extent of litterfall responses to N
366
addition differ among different forest ecosystems and are determined by the amount and duration of N
367
addition.
368
Effect of nitrogen addition on soil respiration and biochemical properties
369
In this forest, we observed that four years of N addition significantly reduced soil respiration,
370
which is consistent with many other studies (Mo et al., 2008; Maaroufi et al., 2015; Zhou et al., 2018;
371
Peng et al., 2018). Soil CO2 efflux is mainly from two sources: root respiration (rhizospheric 13
372
respiration) and microbial decomposition of SOM (heterotrophic respiration), and the latter is
373
considered the basal respiration (Kuzyakov, 2006). In another similar forest in the same region, it was
374
reported that SOM-derived CO2 fluxes accounted for 75% of the total soil CO2 emission and that N
375
addition reduced both rhizospheric and heterotrophic respiration (Peng et al., 2017). The N-induced
376
reduction in soil respiration suggests that SOM decomposition was inhibited by N addition. On one
377
hand, increased N input may stabilize SOM and enhance its resistance to microbial decomposition by
378
incorporating part of the inorganic N into SOM, forming some recalcitrant compounds, such as indoles
379
and pyrroles (Thorn and Mikita, 1992; Riggs et al., 2015). In their work Berg and Matzner (1997) also
380
proposed that N can regulate the accumulation of SOM, as N-containing compounds can polymerize
381
with aromatic substances in the soil to form recalcitrant organic matter. On the other hand, many
382
previous studies demonstrated that N addition negatively affected soil microbial biomass (Treseder,
383
2008; Frey et al., 2014; Peng et al., 2017), which would directly lead to a decrease in SOM degradation.
384
However, in this study, the soil MBC and MBN did not significantly respond to N additions, which
385
may imply that N application had little effect on soil microbial biomass in this forest. Therefore, the
386
SOM decomposition rate in this study may be predicted to decline mainly due to the enhanced
387
stabilization of SOM. In this region, a negative response of root biomass to N addition was also
388
observed in other similar forests (Peng et al., 2017; Zhou et al., 2018). Thus, we hypothesize that a
389
similar response of root biomass would also occur in this forest, which thereby contributes some extent
390
to the decline of soil CO2 efflux.
391
In the present study, the soil TOC concentration in the organic horizon in subplots without litter
392
manipulations significantly increased as N input was elevated. This result may indicate that N addition
393
results in an increase in soil C in topsoil. Globally, increased N deposition is believed to promote
394
terrestrial ecosystems C sequestration because N is considered a limiting nutrient for terrestrial
395
ecosystems (Wang and Houlton, 2009; Norby et al., 2010). Numerous previous studies have
396
demonstrated that N addition resulted in an increase in soil C sequestration in different types of forest
397
(Field et al., 2017; Yue et al., 2017; Forstner et al., 2018; Yan et al., 2018). Wang et al. (2017) assessed
398
that the globally averaged increase in forest C storage due to atmospheric N deposition for 1997-2013
399
was 0.27 ± 0.13 Pg C yr−1, and 29% (0.079 ± 0.034 Pg C yr−1) of that C was stored in forest soil. Two
400
possible reasons can explain this increase in forest soil C storage. First, elevated N deposition increases
401
N availability and then mitigates N limitation of a forest, which in turn boosts forest productivity and, 14
402
subsequently, increases the inputs of organic matter from plant litter (Li et al., 2010a; Field et al., 2017).
403
Second, N addition may suppress SOM decomposition (Riggs et al., 2015; Zang et al., 2016) and thus
404
increase soil C storage. However, in this forest, no significant change was observed in aboveground
405
litter mass after N application; thus, we speculated that the N-induced increase in TOC concentration in
406
organic soil was mainly due to suppressed SOM decomposition rather than boosted forest productivity
407
(Frey et al., 2014). Although a slight increase in ROC concentration in organic soil was observed in this
408
forest, the proportion of ROC in soil TOC is so small (only ~0.03%) that the influence of changes in
409
ROC may be negligible.
410
Surprisingly, we observed that the soil TN concentration in this forest was 41.9 g kg−1 in organic
411
soil, which is much greater than that in other (sub-)tropical forests (Mo et al., 2008; Cusack et al.,
412
2011). One important cause may be the high ambient atmospheric N deposition rate (95 kg N ha−1 yr−1,
413
Xu et al., 2013b), which would lead to accumulation of N in topsoil in this region. In this forest, the LN
414
treatment showed little effect on the soil inorganic N (NH4+ and NO3−) concentration, while the HN
415
treatment considerably increased the soil inorganic N concentration in both soil layers, but no changes
416
were observed in soil TN concentration. There is no doubt that soil NH4+ and NO3− concentrations
417
would increase after a large amount of N input, as NH4NO3 was directly added to the soil surface when
418
performing the N application. Moreover, heightened soil inorganic N concentration is considered to
419
potentially stimulate the process of mineral N production (N mineralization and nitrification) and
420
restrain microbial N immobilization (Baldos et al., 2015), which in turn would increase soil inorganic
421
N concentration. As a result of stimulated nitrification, more protons (H+) may be accumulated in the
422
soil in N-added plots, leading to stronger soil acidification (Peng et al., 2017). In our study, a reduction
423
in soil pH in both organic and mineral horizons was observed. This pattern is corroborated by many
424
studies by our group or others
425
to the high atmospheric N deposition, soils in this region likely show greater N concentration and lower
426
pH compared with other subtropical forests.
(Peng et al., 2017, 2018; Zhou et al., 2018; Forstner et al., 2018). Due
427
In this study, the C pool in mineral soil did not respond to N addition, whereas the soil TOC and
428
ROC concentrations and the C:N ratio in the organic horizon were significantly associated with
429
elevated N input. Therefore, it can be suggested that organic soil is more sensitive to N addition than
430
mineral soil. Previous studies also revealed that simulated N deposition showed a stronger effect on the
431
organic layer C pool than on mineral soil (Frey et al,. 2014; Tonitto et al., 2014; Maaroufi et al., 2015). 15
432
For example, Frey et al. (2014) reported that N addition (50 kg N ha−1 yr−1) significantly increased the
433
SOC in organic soil in both hardwood and pine stands but did not affect that in mineral soil.
434
Effect of aboveground litter alteration on soil respiration and biochemical
435
properties
436
Although soil C is mostly composed of root-derived C (Rasse et al., 2005), litterfall is also well
437
known as an important source of carbon and nutrients returning from vegetation to topsoil ( Rasse et al.,
438
2005; Jia et al., 2018); thus, changes in litterfall input would impact topsoil substrate and nutrient
439
availability and ultimately affect microbial community and carbon dynamics in topsoil (Xu et al.,
440
2013a; Lajtha et al., 2014a, 2014b, 2018; Wu et al., 2017; Cusack et al., 2018). In general, soil
441
respiration, soil microbial biomass, and soil total C and N are considered to be positively correlated
442
with the amount of litterfall input (Xu et al., 2013a). For instance, many previous litter manipulation
443
experiments and meta-analyses reported that aboveground litter removal and addition respectively
444
decreased and increased soil respiration to varying degrees (Sayer et al., 2011; Leff et al., 2012; Xu et
445
al., 2013a; Han et al., 2015; Wu et al., 2017; Chen and Chen, 2018). In this study, the soil respiration
446
rate increased with the increase of aboveground litter input, showing a positive power correlation with
447
litterfall, although the difference in soil respiration between the litter control and L− or L+ did not
448
reach a significant level. These minor changes are likely because only 50% of the litterfall was
449
removed from L− subplots and added to L+ subplots, which is a smaller alteration in litterfall
450
compared to most other experiments conducted in different forests (Sayer et al., 2011; Leff et al., 2012;
451
Han et al., 2015; Bréchet et al., 2018). However, due to the large difference in the amount of litterfall
452
input between L− and L+, a significant difference in the cumulative CO2 effluxes between them was
453
observed. In this study, the effect of litterfall alteration on soil respiration is most likely due to the
454
direct change of substrate-input but not caused by other biotic (e.g., microbial biomass) and abiotic
455
(e.g., temperature and moisture) factors, because those factors were not affected by altered litter-input.
456
During the decomposition process, plant litter releases most C into air, but a few organic C into
457
the surface soil, and most models assumed a direct relationship between litter input and soil C storage
458
(Gottschalk et al., 2012). Therefore, it was generally considered that surface soil C content would be
459
associated with the amount of litter input (Lajtha et al., 2018). Many studies did demonstrate that
460
long-term litter removal reduced soil C content in topsoil and litter addition enhanced the C content 16
461
(Lajtha et al., 2014a; Cusack et al., 2018). Litter removal likely leads to a decline in soil C in most
462
forests, while litter addition might not always positively affect soil C and showed little and even
463
negative effects on soil C in some ecosystems (Bowden et al., 2014; Lajtha et al., 2014b, 2018). This
464
minor change in soil C content after increased litter input can be mainly explained by the priming effect
465
because the enhanced soil C derived from increased plant litter may be offset by the accelerated
466
decomposition of native SOM (Sayer et al., 2011; Xu et al., 2013a). In this study, although we did not
467
observe that litter addition changed soil C concentration, there was no evidence that the priming effect
468
played an important role in this process because the soil CO2 efflux in the L+ subplots did not
469
significantly differ from that in the litter control. In addition, there were also no differences in soil C
470
between the L− and litter control subplots and in other soil properties among litter manipulations.
471
Therefore, we attributed these unaffected results to the smaller alteration of litterfall input (only 50%)
472
and shorter experiment duration (< 2.5 years) compared to other studies, in which litters were doubled
473
or entirely excluded continually for 10 or more years (Lajtha et al., 2014a; Cusack et al., 2018). Other
474
short-term experiments also reported a similar result: minor changes were observed in soil C and N
475
contents after less than 5 years of litter treatment (Holub et al., 2005; Zhao et al., 2017). Because the
476
effect of litter manipulation on soil may have a significant temporal lag (Lajtha et al., 2014b),
477
long-term observation (decadal-scale) is necessary to investigate the response of soil to altered litter
478
input (Sayer, 2005; Lajtha et al., 2018), especially in experiments with small proportions of litter
479
manipulation.
480
Effect of aboveground litter manipulation on soil respiration and biochemical
481
properties under different nitrogen-addition conditions
482
Our data indicated that, under each N-addition condition, soil respiration increased with increasing
483
aboveground litter input. Combined N addition and litter reduction significantly decreased soil
484
respiration and showed a stronger effect than individual N addition or litterfall reduction. This pattern
485
occurs because both N addition and litterfall reduction can cause a decrease in soil CO2 efflux, as
486
discussed before (Leff et al., 2012; Han et al., 2015; Wu et al., 2017; Peng et al., 2018; Zhou et al.,
487
2018). However, the soil C content in subplots treated with a combination of N addition and litter
488
reduction showed no significant change compared to subplots without N addition and litter alteration,
489
which might suggest that an N-induced increase in soil C content may be partly offset by decreased 17
490
litter input. Conversely, combined N and litter addition did not significantly affect soil CO2 effluxes,
491
which indicated that litter addition likely mitigated the negative response of soil respiration to N
492
addition because soil respiration is positively associated with litterfall (Sayer et al., 2011; Leff et al.,
493
2012; Han et al., 2015; Wu et al., 2017).
494
Surprisingly, no changes were observed in soil TOC concentration among litterfall manipulations
495
in N control plots, but both the L− and L+ treatments were found to significantly reduce soil TOC in
496
the organic horizon in N-added plots, which may suggest that topsoil C content is sensitive to
497
alterations of aboveground litter input when N input is elevated. This relation would have important
498
implications on the response of soil C storage to global change. In the HN treatment plots, L−
499
significantly reduced the soil TOC concentration in organic soil by 10.7% relative to L0. Firstly,
500
reduced litterfall directly results in a reduction in aboveground C input. In addition, previous studies
501
have noted that reduced aboveground litter input can potentially lead to a decrease in root biomass and
502
production, which is an important soil C source (Rodtassana and Tanner, 2018). Therefore, it can be
503
surmised that a reduction in aboveground litter in HN plots may lead to a decreased soil C content by
504
reducing aboveground C input directly and by reducing belowground C input indirectly. Unexpectedly,
505
the L+ treatment was observed to reduce the surface soil TOC by ~13% compared with L0 in N-added
506
plots. Many studies demonstrated a neutral or even negative effect of litter addition on soil C content as
507
a result of higher rates of SOM degradation due to a priming effect (Sayer et al., 2011; Leff et al., 2012;
508
Zhang et al., 2017; Pisani et al., 2016). However, in this study, the soil CO2 efflux in L+ did not
509
significantly differ from L0 in N-added plots, which did not support the priming effect; thus, the
510
potential mechanism needs further research.
511
Our results showed that L− significantly increased soil NH4+ concentration in topsoil in N-added
512
plots but not in plots without N addition, while L+ did not affect that factor in plots either with or
513
without N addition. Similarly, Holub et al. (2005) also reported that soil NH4+ concentration under high
514
N deposition was greater in plots with no litter input compared to intact litter plots but did not change
515
in doubled litter plots or under low N deposition. Because the litter layer acts as a kind of buffer and
516
barrier which regulates nutrients the underlying horizon will receive from precipitation, part of the
517
NH4+ added to the surface of the litter cannot reach mineral soil but is retained in the litter layer.
518
Therefore, it is logical that the smaller the amount of litter above the soil, the more the proportion of
519
the added NH4+ that will reach the soil. Additionally, as C:N ratio in litter is generally higher than that 18
520
in microbes, a litter net N immobilization commonly occurs in terrestrial ecosystems (Holub et al.,
521
2005; Parton et al., 2007). In this study, because of decreased litter input, immobilization of added
522
NH4+ was also decreased; thus, more NH4+ was retained in the soil of L− subplots compared to litter
523
intact subplots. However, the little change in soil NH4+ concentration in L+ subplots was probably due
524
to the limitation of microbes in the topsoil and litter layer.
525
Conclusion
526
Our results highlight that elevated N input significantly increased the surface soil C content by
527
suppressing soil respiration mainly due to enhanced stabilization of SOM rather than decreased soil
528
microbial biomass. Due to the smaller alteration and shorter experimental duration, the aboveground
529
litter manipulation did not affect any soil properties characterized in this study, but the soil CO2
530
emission was significantly associated with the amount of litter input. Because of temporal lag, a
531
long-term litter manipulation experiment is necessary to investigate the response of soil to altered litter
532
input. Aboveground litter reduction likely promotes a negative effect on soil respiration due to N
533
addition, while litter addition tended to mitigate the change in soil respiration. Under N addition, litter
534
reduction tended to decrease the surface soil C content by reducing the aboveground C input directly
535
and the belowground C input indirectly. Aboveground litter addition also tended to reduce the topsoil C
536
content when the N input is enhanced, but the potential mechanism still needs further exploration
537
because no evidence was observed to support a priming effect. Both N and aboveground litter
538
manipulations showed a stronger effect on the organic soil layer than on the mineral soil layer. Finally,
539
because the soil in this forest shows very high N content and is probably already N-saturated, as a
540
result of the high ambient atmospheric N deposition rate here, some of our results would not apply for
541
forests not (or less) affected by this situation.
542 543 544 545 546
Acknowledgement This project was supported by the National Natural Science Foundation of China (No. 31300522) and Major Project of Education Department in Sichuan Province (No. 17ZA0310).
547
19
548
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549
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Figure legends:
788 789
Figure 1 Location of study site in Ya’an, Sichuan province, China and the schematic design of N
790
addition and aboveground litter manipulation. CN, LN and HN indicate N control (ambient N
791
input), low level (+ 50 kg N ha−1 year−1) and high level (+ 150 kg N ha−1 year−1) of N addition,
792
respectively. L0, L− and L+ indicate natural litter input, aboveground litter reduction (reduced by 50%)
793
and addition (increased by 50%), respectively.
794 795
Figure 2 Seasonal variations in above-ground litter input in an evergreen broad-leaved forest in
796
southwestern China from August 2015 to December 2017. Histograms indicate cumulative litter
797
input in each year (litter traps were set in the end of July 2015, thus only last five months were included
798
in 2015) and total input of all the months. Values are means, n=4. Error bars were not given to improve
799
the clearness of the graph. The results of repeated measures ANOVA are shown. CN: N control
800
(ambient N input); LN: low level of N addition (+ 50 kg N ha−1 year−1); HN: high level of N addition
801
(+ 150 kg N ha−1 year−1).
802 803
Figure 3 Seasonal variations in soil temperature (A) and soil moisture content (B) in an evergreen
804
broad-leaved forest in southwestern China from January 2016 to December 2017. Values are
805
means, n=4. Error bars were not given to improve the clearness of the graph. CNL−: Nitrogen control
806
with litter reduction; LNL−: Low N addition with litter reduction; HNL−: High N addition with
807
litter reduction; CNL0: Nitrogen control with intact litter input; LNL0: Low N addition with
808
intact litter input; HNL0: High N addition with intact litter input; CNL+: Nitrogen control with
809
litter addition; LNL+: Low N addition with litter addition; HNL+: High N addition with litter
810
addition.
811 812
Figure 4 Seasonal variations in soil respiration in an evergreen broad-leaved forest in
813
southwestern China from January 2016 to December 2017. Values are means, n=4. Error bars
814
were not given to improve the clearness of the graph. CNL−: Nitrogen control with litter
815
reduction; LNL−: Low N addition with litter reduction; HNL−: High N addition with litter 28
816
reduction; CNL0: Nitrogen control with intact litter input; LNL0: Low N addition with intact
817
litter input; HNL0: High N addition with intact litter input; CNL+: Nitrogen control with litter
818
addition; LNL+: Low N addition with litter addition; HNL+: High N addition with litter
819
addition.
820 821
Figure 5 Cumulative CO2 flux under different treatments. CNL−: Nitrogen control with litter
822
reduction; LNL−: Low N addition with litter reduction; HNL−: High N addition with litter
823
reduction; CNL0: Nitrogen control with intact litter input; LNL0: Low N addition with intact
824
litter input; HNL0: High N addition with intact litter input; CNL+: Nitrogen control with litter
825
addition; LNL+: Low N addition with litter addition; HNL+: High N addition with litter addition.
826
Error bars indicate ± 1SE, n=4. Different letters indicate significant difference among different N
827
additions and litter manipulations within each year.
828 829
Figure 6 Relationships between soil respiration and soil temperature (A) and litterfall (B). Values
830
are means, n=4. Error bars were not given to improve the clearness of the graph. CNL−: Nitrogen
831
control with litter reduction; LNL−: Low N addition with litter reduction; HNL−: High N
832
addition with litter reduction; CNL0: Nitrogen control with intact litter input; LNL0: Low N
833
addition with intact litter input; HNL0: High N addition with intact litter input; CNL+: Nitrogen
834
control with litter addition; LNL+: Low N addition with litter addition; HNL+: High N addition
835
with litter addition.
29
1
Influences of nitrogen addition and aboveground litter-input manipulations on soil respiration
2
and biochemical properties in a subtropical forest
3 4 5 Table 1 Results of repeated measures ANOVA concerning the effects of sampling time, nitrogen treatment, litter manipulation, and their interactions on soil temperature and soil moisture in an evergreen broad-leaved forest in southwestern China from January 2016 to December 2017 Temperature (ºC)
Factors
Moisture (%)
df
F-value
P-value
df
F-value
P-value
Time (T)
23
8507.256
< 0.001
23
10.863
< 0.001
Nitrogen (N)
2
2.056
0.148
2
1.303
0.319
Litter (L)
2
0.944
0.402
−
−
−
N×L
4
0.327
0.857
−
−
−
T×N
46
0.724
0.747
46
0.963
0.485
T×L
46
0.607
0.855
−
−
−
T×N×L
92
0.635
0.921
−
−
−
Soil moistures for subplots with litter manipulations were not measured, thus effect of litter alteration on soil moisture was not shown.
6 7 8 Table 2 Results of two-way repeated measures ANOVA concerning the effects of sampling time, nitrogen treatment, litter manipulation, and their interactions on soil respiration in an evergreen broad-leaved forest in southwestern China from January 2016 to December 2017 Factors
2016
2017
Whole study period
df
F-value
P-value
df
F-value
P-value
df
F-value
P-value
Time (T)
11
175.214
< 0.001
11
166.122
< 0.001
23
166.315
< 0.001
Nitrogen (N)
2
12.038
< 0.001
2
7.641
0.002
2
10.854
< 0.001
Litter (L)
2
7.078
0.003
2
4.969
0.015
2
6.765
0.004
N×L
4
0.957
0.447
4
0.755
0.564
4
0.891
0.483
T×N
22
1.568
0.109
22
2.062
0.063
46
1.788
0.065
T×L
22
1.679
0.079
22
1.227
0.299
46
1.290
0.239
T×N×L
44
0.868
0.642
44
0.787
0.668
92
0.779
0.740
9
1
Table 3 Averaged soil properties for four times and P-value of two-way repeated ANOVA focus on effects of sampling time, N addition, litter manipulation, and their interactions on soil chemistry TOC (g kg−1)
ROC (mg kg−1)
EDOC (mg kg−1)
TN (g kg−1)
NO3− (mg kg−1)
Factors
Organic horizon
Mineral horizon
Organic horizon
Mineral horizon
Organic horizon
Mineral horizon
Organic horizon
Mineral horizon
Organic horizon
Mineral horizon
CNL−
174.8 ± 5.1 bc
30.5 ± 2.0
53.1 ± 1.7 ab
9.4 ± 1.0
0.34 ± 0.03
0.37 ± 0.06
47.1 ± 0.9
10.3 ± 0.6
46.4 ± 1.2 e
27.9 ± 7.0 c
CNL0
167.6 ± 6.1 bc
28.3 ± 1.7
49.8 ± 2.0 b
9.0 ± 0.8
0.32 ± 0.03
0.40 ± 0.04
41.9 ± 1.4
9.5 ± 0.7
50.8 ± 4.5 e
24.8 ± 3.8 c
CNL+
160.7 ± 2.1 c
28.8 ± 1.5
52.0 ± 2.2 ab
9.6 ± 0.9
0.33 ± 0.01
0.35 ± 0.06
43.3 ± 1.5
10.0 ± 0.6
50.4 ± 3.2 e
26.5 ± 2.1 c
LNL−
161.4 ± 12.8 bc
29.9 ± 3.5
52.1 ± 3.4 ab
9.6 ± 1.4
0.33 ± 0.05
0.32 ± 0.03
44.8 ± 3.1
10.8 ± 0.8
69.1 ± 9.5 bcd
35.0 ± 3.1 bc
LNL0
179.5 ± 7.0 b
28.8 ± 1.3
57.8 ± 2.4 a
9.3 ± 0.8
0.33 ± 0.01
0.35 ± 0.05
45.1 ± 2.1
9.8 ± 0.2
57.7 ± 4.4 de
27.1 ± 2.7 c
LNL+
155.6 ± 9.5 c
28.6 ± 2.2
52.9 ± 1.3 ab
10.5 ± 1.3
0.30 ± 0.04
0.32 ± 0.03
44.1 ± 0.8
10.0 ± 0.4
63.0 ± 5.2 cde
31.8 ± 5.5 c
HNL−
177.0 ± 3.5 bc
29.5 ± 3.5
59.5 ± 1.8 a
9.4 ± 0.7
0.33 ± 0.04
0.40 ± 0.05
44.3 ± 0.8
10.1 ± 0.8
86.5 ± 8.9 a
53.6 ± 9.3 a
HNL0
198.2 ± 4.1 a
29.5 ± 3.4
57.9 ± 4.2 a
9.5 ± 1.3
0.33 ± 0.04
0.40 ± 0.05
45.1 ± 1.1
9.7 ± 0.6
84.1 ± 6.5 ab
56.0 ± 8.7 a
HNL+
173.1 ± 4.7 bc
26.1 ± 2.2
59.0 ± 3.1 a
8.9 ± 0.7
0.35 ± 0.06
0.38 ± 0.03
44.9 ± 1.0
9.2 ± 0.6
78.7 ± 4.5 abc
51.9±5.5ab
Time (T)
< 0.001
0.567
< 0.001
< 0.001
< 0.001
< 0.001
< 0.001
< 0.001
< 0.001
< 0.001
Nitrogen (N)
0.009
0.905
0.008
0.775
0.865
0.319
0.863
0.552
< 0.001
< 0.001
Litter (L)
0.009
0.601
0.971
0.904
0.959
0.727
0.506
0.315
0.745
0.821
N×L
0.283
0.951
0.456
0.915
0.983
0.996
0.347
0.912
0.639
0.918
T×N
0.376
0.504
0.242
0.511
0.575
0.413
0.662
0.226
< 0.001
0.277
T×L
0.499
0.949
0.614
0.123
0.935
0.792
0.174
0.223
0.556
0.792
T×N×L
0.610
0.919
0.855
0.728
0.966
0.986
0.255
0.946
0.520
0.657
2
(Continued) NH4+ (mg kg−1)
MBC (mg kg−1)
MBN (mg kg−1)
C : N ratio
pH
Factors
Organic horizon
Mineral horizon
Organic horizon
Mineral horizon
Organic horizon
Mineral horizon
Organic horizon
Mineral horizon
Organic horizon
Mineral horizon
CNL−
20.1 ± 4 4 d
12.4 ± 2.4 c
1.46 ± 0.24
0.33 ± 0.03
0.27 ± 0.03
0.067 ± 0.012
3.70 ± 0.11 bc
2.98 ± 0.12
3.45 ± 0.03 abc
3.91 ± 0.05 a
CNL0
19.0 ± 4.4 d
15.0 ± 1.3 c
1.32 ± 0.18
0.32 ± 0.06
0.25 ± 0.03
0.077 ± 0.010
3.99 ± 0.11 b
3.04 ± 0.07
3.52 ± 0.03 a
3.90 ±0.03 a
CNL+
19.2 ± 3.8 d
12.8 ± 1.8 c
1.12 ± 0.26
0.37 ± 0.04
0.24 ± 0.03
0.070 ± 0.00
3.70 ± 0.15 bc
2.89 ± 0.12
3.52 ± 0.03 a
3.91 ± 0.04 a
0.37 ± 0.05
0.24 ± 0.02
0.064 ± 0.01
LNL−
42.4 ± 4.9 c
15.6 ± 2.3 c
1.11 ± 0.09
3.58 ± 0.06 c
2.73 ± 0.14
3.40 ± 0.04 bcd
3.84 ± 0.02 ab
LNL0
19.9 ± 4.4 d
15.0 ± 1.2 c
0.99 ± 0.20
0.33 ± 0.03
0.21 ± 0.03
0.089 ± 0.02
4.00 ± 0.12 b
2.96 ± 0.09
3.47 ± 0.05 ab
3.86 ± 0.04 a
LNL+
17.9 ± 3.7 d
13.7 ± 1.3 c
0.98 ± 0.14
0.34 ± 0.03
0.19 ± 0.02
0.069 ± 0.01
3.52 ± 0.16 c
2.84 ± 0.10
3.45 ± 0.02 abc
3.87 ± 0.04 a
HNL−
69.6 ± 9.9 a
27.2 ± 3.2 ab
1.08 ± 0.22
0.31 ± 0.05
0.19 ± 0.03
0.050 ± 0.01
4.02 ± 0.17 b
2.92 ± 0.09
3.35 ± 0.03 d
3.74 ± 0.03 c
HNL0
53.4 ± 3.6 bc
25.1 ± 1.4 b
0.97 ± 0.07
0.29 ± 0.03
0.19 ± 0.03
0.063 ± 0.00
4.43 ± 0.13 a
3.33 ± 0.47
3.36 ± 0.03 cd
3.71 ± 0.03 c
HNL+
62.3 ± 6.8 ab
31.6 ± 1.5 a
0.95 ± 0.19
0.35 ± 0.07
0.20 ± 0.02
0.060 ± 0.01
3.85 ± 0.19 bc
2.86 ± 0.10
3.37 ± 0.04 cd
3.75 ± 0.03 bc
Time (T)
< 0.001
< 0.001
< 0.001
< 0.001
< 0.001
< 0.001
< 0.001
0.002
< 0.001
< 0.001
Nitrogen (N)
< 0.001
< 0.001
0.112
0.704
0.053
0.119
0.004
0.434
< 0.001
< 0.001
Litter (L)
0.013
0.773
0.432
0.543
0.621
0.168
0.001
0.202
0.146
0.718
N×L
0.177
0.178
0.970
0.950
0.962
0.918
0.878
0.820
0.900
0.972
T×N
< 0.001
<0.001
0.454
0.397
0.576
0.753
0.134
0.521
0.075
0.016
T×L
< 0.001
0.009
0.951
0.596
0.751
0.296
0.008
0.061
0.309
0.558
T×N×L
0.175
0.525
0.999
0.983
0.851
0.645
0.623
0.517
0.655
0.999
CNL−: Nitrogen control with litter reduction; LNL−: Low N addition with litter reduction; HNL−: High N addition with litter reduction; CNL0: Nitrogen control with intact litter input; LNL0: Low N addition with intact litter input; HNL0: High N addition with intact litter input; CNL+: Nitrogen control with litter addition; LNL+: Low N addition with litter addition; HNL+: High N addition with litter addition. Different letters indicate significant difference among treatments (P < 0.05)
3