Introduction
Nitrous oxide (N2O) and nitric oxide (NO) are two of the most important
anthropogenic nitrogen compounds emitted to the atmosphere, which are
directly or indirectly involved in global warming and atmospheric chemistry
(Williams et al., 1992; IPCC, 2013). It is well accepted that human
activities strongly influence the source of N2O and NO, as nitrogen
fertilizer applied in agriculture is now the vital source of
inorganic/organic nitrogen substrate for nitrification and denitrification
processes, leading to increased N2O and NO emissions (McElroy and Wang,
2005; Galloway et al., 2008). Recently anthropogenic emissions from the
application of nitrogenous fertilizers in agriculture were estimated to be
1.7–4.8 Tg N yr-1 for N2O and 3.7 Tg N yr-1 for NO,
accounting for approximately 60 and 10 % of the total global
estimates, respectively (IPCC, 2013). However, one should admit that a
dearth of direct measurements of nitrogenous gas fluxes in some
agricultural areas makes these estimates highly uncertain, and it also
results in the projection and mitigation of agricultural N2O and NO
emissions posing considerable challenges (Davidson and Kingerlee, 1997; Reay
et al., 2012), although the measurements of these emissions have been made
for many decades. Taking Stehfest and Bouwman (2006) as an example, they
summarized information from 1008 N2O and 189 NO emission measurements
in agricultural fields worldwide, and indicated that the representation of
number of measurements in tropical and subtropical climates was only
13–14 and 23–28 % for N2O and NO, respectively. As suggested by
Reay et al. (2012), therefore, a central aim of future study on e.g.,
N2O emissions from agricultural systems, should be to increase the
coverage encompassing various agricultural land-use/cover types and climates
as well as management practices.
Tea is one of the three most common beverages (i.e., coffee, tea and cocoa)
worldwide, and tea crops are widely planted in the tropical and subtropical
regions (Xue et al., 2013). China is the world's largest tea-producing
country, and its tea plantation area had reached 1.85 million ha in 2009,
contributing approximately 52 % to the world total (Han et al., 2013a).
In addition, tea is a leaf-harvested crop, and nitrogen is the most important
nutrient for increasing the content of free amino acids, an index of the
quality of tea leaves (Tokuda and Hayatsu, 2004). For improving the yield
and quality of tea leaves, therefore, large amounts of nitrogen fertilizer
are increasingly applied by tea farmers. For instance, the application rates
of nitrogen fertilizer to tea plantations have been as high as 450–1200 kg N ha-1 yr-1,
which significantly surpasses the recommended rate of
250–375 kg N ha-1 yr-1 for high tea yields (Tokuda and Hayatsu,
2004; Hirono and Nonaka, 2012; Fu et al., 2012; Zhu et al., 2014). Not
surprisingly, such high nitrogen inputs can easily induce excess residual
nitrogen and acidification of soil; both influence the nitrogen cycle of tea
fields in which a great deal of nitrogenous gases are produced (Jumadi et
al., 2008; Zhu et al., 2014) . It was reported that the N2O emissions
from tea fields were greatly higher than those from other upland fields
(Jumadi et al., 2005; Han et al., 2013a). Akiyama et al. (2006) analyzed
data on N2O emissions from 36 sites with 246 measurements in Japanese
agricultural fields and reported that the mean fertilizer-induced emission
factor of N2O in tea fields was much higher as compared to other upland
fields and paddy fields. Nevertheless, there are still very few data
available on N2O emissions from Chinese tea plantations (Fu et al.,
2012; Li et al., 2013; Han et al., 2013a). Meanwhile, tea plantations to
which large amounts of nitrogen fertilizer have been added are also probably
one of the important sources of NO. So far, however, no study is available
for NO fluxes from tea fields worldwide, which hinders the development of
a sound NO emission inventory (Huang and Li, 2014).
As tea production in China has intensified to meet market demands over the
past decades, public concerns over the negative impacts of conventional
synthetic nitrogen fertilizers application in tea plantations on human
health and environmental quality have also increased (Pimentel et al., 2005;
Han et al., 2013b). These concerns have led to increased grower interest in
organically fertilized tea plantations, and by 2011 approximately 45 000 ha
of tea fields were under organic fertilization in China (Han et al., 2013b).
Furthermore, the conversion of conventional synthetic nitrogen fertilization
to organic fertilizer practice in tea plantations has been identified as a
feasible measure in the aspects of promoting soil carbon sequestration and
ameliorating soil pH (Han et al., 2013b; Wang et al., 2014). On the other
hand, organic fertilization systems have been shown to substantially affect
N2O emissions compared with conventional management practices, but the
influence can be either stimulatory (Akiyama and Tsuruta, 2003a, b;
Syväsalo et al., 2006) or marginal and even inhibitory (Akiyama and
Tsuruta, 2003b; Burger et al., 2005; Petersen et al., 2006; Kramer et al.,
2006). Although these studies have demonstrated that organic fertilizer practices
may improve soil quality and influence nitrogenous gas fluxes in some
agricultural systems, no study has specifically compared N2O and NO
emissions in response to organic and synthetic nitrogen fertilizer
application in tea plantations to our knowledge.
In this paper, we present the results of a 2-year field study in which
N2O and NO fluxes were measured simultaneously in Chinese subtropical
tea plantations under three practices of conventional urea application,
alternative organic fertilizer incorporation and no nitrogen fertilization.
The main objectives of the present study were to characterize and quantify
annual N2O and NO fluxes and their direct emission factors across
different years, and to evaluate the effect of organic fertilizer management
on N2O and NO fluxes as well as to clarify the underlying mechanisms
and factors regulating these fluxes from tea plantations.
Materials and methods
Site description and field treatments
Field measurements were carried out in a tea planting farm (32∘07′22′′ N,
110∘43′11′′ E; approx. 441 m above sea level)
of the Agricultural Bureau of Fangxian, Hubei province, China. The
region is characterized by a northern subtropical monsoon climate with cool
and dry winters as well as warm and humid summers. From 2003 to 2011, the
mean annual precipitation and air temperature for this site were 914 mm and
14.2 ∘C, respectively. Before the campaign of tea cultivations,
all fields in this area had been cultivated with rice–fallow or rice–oilseed
rape rotation cropping system. The tea plants in the experimental field were
transplanted in March 2008; thereafter it has been continuously cultivated
with regular synthetic nitrogen fertilizers and irrigation additions
according to common regional management practice. The topsoil (0–15 cm) of
the experimental site is of a loamy texture with (mean ± SE, n= 12)
12.7 ± 0.1 % clay (< 0.002 mm), 39.3 ± 0.5 % silt
(0.002–0.02 mm), and 48.0 ± 0.6 % sand (0.02–2 mm). Other important
soil physiochemical properties include organic carbon content of 13.6 ± 0.2 g kg-1,
total nitrogen content of 1.5 ± 0.1 g kg-1, pH of
5.0 ± 0.1, and bulk density of 1.25 ± 0.03 g cm-3.
Our field study was performed over the course of 2 consecutive years from
September 2012 to October 2014. As shown in Table 1, three experimental
treatments were set up on the tea (T) field with an approximately 4-year-old
plantation: one with the addition of urea (UN) that is the local farmer's
conventional and common practice for this region, another with the application
of organic fertilizer (OM) that is likely to be used as an alternative practice in
the future for this region, and the final treatment with no application of synthetic
nitrogen fertilizers or organic fertilizers (NN). These
fertilizer treatments were arranged in a randomized complete block design
with four replicates, resulting in a total of 12 plots (each with an area of
8 m × 8 m). For the TUN (tea field plus urea) plots, urea was applied at the common rate
of 450 kg N ha-1 yr-1 in two splits (one-third of annual nitrogen
inputs as basal fertilization in the autumn time, two-thirds as top dressing
in the spring time). With respect to TOM (tea field plus organic fertilizer), organic fertilizer was applied at
rates and times in accordance with TUN (Table 1). The form of fertilizer
applied in TOM was oilcake, which is a typical organic fertilizer in tea
cultivations of China and other countries like Japan. This organic
fertilizer contained 7.1 % N and had a C : N ratio of 6.1. In addition, all
treatments received equal amounts of phosphorous and potassium (i.e., 225 kg
P2O5 ha-1 yr-1 and 225 kg K2O ha-1 yr-1)
in terms of fertilizer recommendations by local farmers. On each replicated
plot, the width of the canopy of tea plants was approximately 0.5 m, and the
distance of inter-row space between the canopies was about 0.4 m. All of the
fertilizers were applied as band application in the inter-row space between
canopies with widths of approximately 0.2 m, and then incorporated into
soils with a depth of approximately 0.1 m, which is the conventional
practice in tea cultivations. Due to the young plantation age, the present
tea plants did not receive any trimming during the experimental period, and
they also seldom experienced leaf harvest.
Field management of synthetic and organic nitrogen fertilizers for
tea plantations under different treatments during the period of 2012–2014.
Nitrogen application rate (kg N ha-1)
Application date
TNN
TUN
TOM∗
Basal fertilization
0
Urea (150)
Oilcake (150)
8 Oct (2012), 6 Oct (2013)
Topdressing
0
Urea (300)
Oilcake (300)
18 Feb (2013), 1 Mar (2014)
Total
0
450
450
* The fertilizer of oilcake contained 7.1 % N and had a C : N ratio
of 6.1.
Measurements of N2O and NO fluxes
The fluxes of N2O and NO were measured simultaneously in situ using
manually closed chamber-based techniques (Zheng et al., 2008; Yao et al.,
2009). As mentioned above, all fertilizers were incorporated in the form of
bands between the rows of tea plants, and the remaining area was covered by
canopy under which no fertilizer was applied. To better evaluate gas fluxes
from the tea field, a size of rectangular stainless-steel frame of 0.70 m × 0.90 m
(width ×length) was set up in each replicated
plot, which covered four tea plants and parts of spaces between rows; that
is, the frame covered the whole canopy area (i.e., 0.5 m in length) and
two halves of the fertilized inter-row spaces on both sides of the tea canopy
(i.e., 0.2 m in length each side), representing the whole tea field
landscape. To eliminate the possibility of influence on N2O and NO
fluxes from the temporary installation of chamber bases (Matson et al.,
1990), the frames were inserted into the soil to a depth of 0.15 m 1 month
before the start of flux measurements, and they were maintained in place
throughout the entire observation period, except when they were removed for
necessary farming practices (e.g., band fertilization). Further, the
sampling locations were connected with boardwalks to prevent soil
disturbance during the sampling period. In general, flux measurements were
conducted five times per week during the first week after each fertilization
event, and three times per week during the rest of time. Almost all of the
gas sampling was taken between 09:00 and 11:00 local standard time (LST) on each
measuring day to minimize the influence of diurnal temperature variation.
Based on the size of frames and the height of tea plants, insulated chambers
with a bottom area of 0.70 m × 0.90 m and a height of 1.0 m were
designed for gas samplings. These chambers were wrapped with a layer of
styrofoam and aluminum foil to minimize temperature changes during the
sampling period. Also, two circulating fans driven by 12V DC were installed
inside the sampling chamber to facilitate mixing of chamber air and thus
inhibiting the formation of gas concentration gradients, and a hole of 2 cm
diameter was fitted in the top panel for equilibrating the pressure during
the placement of them on the base frames. This hole was embedded during the
gas sampling using a pressure balance tube whose diameter and length were
determined according to the recommendation of Hutchinson and Mosier (1981).
To acquire the N2O flux, five gas samples were withdrawn from the
chamber headspace using 60 mL polypropylene syringes fitted with three-way
stopcocks at fixed intervals of 0, 10, 20, 30, and 40 min after covering.
Within 3 h after collection, the N2O concentrations of gas samples
stored in airtight syringes were directly analyzed in the laboratory
established beside the experimental field, using a gas chromatograph (GC,
Agilent 7890A, Agilent Technologies, CA, USA) equipped with an electron
capture detector at 330 ∘C on the basis of the DN-CO2 method, as
described in detail by Zheng et al. (2008). The N2O was separated by
two stainless steel columns (both with an inner diameter of 2 mm, one with a
length of 1 m and the other with a length of 2 m) packed with Porapak Q,
80/100 mesh at 55 ∘C isothermally. To ensure quality and
stability assurance, five standard N2O samples with concentrations of 350 ppbv (the National Center for Standard
Matters, Beijing, China) were inserted into the GC system between every 10 unknown gas samples. Results of GC
analyses were accepted when five standard gas calibrations produced
coefficients of variation lower than 1 %. The N2O flux was determined
by the linear or non-linear change of gas concentrations during the time of
chamber closure, as described in detail by Wang et al. (2013). In this
study, the minimum detection limit of N2O flux was approximately 2.6 µg N m-2 h-1.
For each NO flux measurement, gas samples were collected from the same
chamber that was used for N2O flux measurements (Yao et al., 2009).
Before closing the chamber, approximately 2.5–3 L gas sample from the
headspace of each chamber was extracted into an evacuated bag made of inert
aluminum-coated plastic, and this measurement was regarded as time 0 min for
NO analysis. After 40 min under chamber enclosure conditions (i.e., after
finishing N2O sample collections), another headspace gas sample with
the same volume was extracted from each chamber into another evacuated bag.
From these bag samples, NO concentrations were analyzed within 1 h by using
a model 42i chemiluminescence NO–NO2–NOx analyzer (Thermo
Environmental Instruments Inc., USA). The NOx analyzer instrument was
calibrated monthly in the laboratory using a TE-146i dilution-titration
instrument (dynamic gas calibrator). A cylinder of standard gas of 50 ppmv
NO in N2 (the national center for standard matters, Beijing, China) and
a zero gas generator (Model 111 Zero Air Supply) were used for multipoint
calibrating, spanning, and zeroing of the NOx analyzer. The NO flux was
determined from the concentration at the end of the chamber enclosure period
by subtracting the concentration at time 0 min. It should be noted that
although some studies deriving N2O and NO fluxes by employing either a
simple linear regression method (e.g., Williams and Davidson, 1993; Kim and
Kim, 2002; Zheng et al., 2003; Venterea et al., 2003; Li and Wang et al.,
2007; Pang et al., 2009; Zhao et al., 2015) or a non-linear regression model
(e.g., Valente et al., 1995; Kroon et al., 2008; Yao et al., 2010a; Wang et
al., 2013) have been widely adopted, it is clear that inappropriate
application of a linear model to non-linear data may seriously underestimate
the trace gas flux (Hutchinson and Livingston, 1993; Kutzbach et al., 2007).
For example, Kroon et al. (2008) suggested that on average, the N2O
emission estimates with the linear regression method were 46 % lower than
the estimates with the exponential regression method. Similarly, Mei et al. (2009)
conducted a field intercomparison of NO flux measurements with linear
and non-linear regression methods, and observed that the linear estimates of
NO flux were 26 % lower on average relative to the non-linear method.
However, to date there has been limited field comparison of these two
methods to assess comparability of N2O or NO fluxes calculated by them.
Based on our data sets of NO measured in wheat fields using the
automatically static translucent chamber-based system (the raw data from the
case studies of Zheng et al., 2003 and Yao et al., 2010a), the NO fluxes
were re-estimated using linear and non-linear regression methods. In order to
better compare the two regression methods, a subset of data collected in the
evening was used that satisfied the present conditions of static opaque
chamber technique. Finally, approximately 3489 pairs of observations were
used for comparing the difference between the two regression methods; and
the results showed that the linear model underestimated the NO fluxes by
3 to 59 % (mean: 31 %) at the 95 % confidence interval, as
compared to the non-linear method. Overall, these findings indicate that data
sets of N2O collected in this study are relatively reliable, but the
present method of linear accumulation assumption inevitably introduces an
extent of underestimation into the NO fluxes for cases with non-linear
accumulations. Therefore, it has to be noted that the NO fluxes reported in
this study represent the conservative magnitude for the present tea
plantations.
Auxiliary measurements
The air temperature inside the chamber headspace during the flux
measurements was recorded with a manual thermocouple thermometer (JM624,
Tianjin, China). Air pressure and temperature as well as daily precipitation
were obtained from an automatic meteorological station set up on the
experimental farm. The air temperature measured in the chamber enclosures
and air pressure obtained from the meteorological station were directly
utilized in the flux computations to calculate the gas density during the
sampling conditions by using the ideal gas law. Soil (5 cm) temperature was
automatically measured in 30 min intervals from the direct vicinity of the
chamber frames using a HOBO temperature sensor (Onset, USA). Soil water
content (0–6 cm) was recorded daily using a portable frequency domain
reflectometry (FDR) probe (MPM-160, China). Three replicate soil samples
(0–10 cm) in each plot were collected at 1–2 week intervals using a 3 cm
diameter gauge auger. Following the collection, the fresh samples were
bulked into one composite sample for each treatment, and then immediately
extracted with 1 M KCl and 0.05 M K2SO4 to determine the
concentrations of soil mineral N (NH4+ and NO3-) and
dissolved organic carbon (DOC), respectively, both with a soil: solution
ratio of 1 : 5. The NH4+, NO3- and DOC concentrations were
measured simultaneously with a continuous flow colorimetric analysis
instrument (San++, Skalar Analytical B.V., Netherlands).
Statistical analysis
Statistical analysis was conducted using the SPSS19.0 (SPSS China, Beijing,
China). Before variance component analysis, all data were tested for normal
distribution using the non-parametric tests approach, and the original data
that failed the test were log-transformed (P= 0.01–0.42). To determine
differences in nitrogenous gas fluxes and soil environmental variables
among treatments during the given pronounced flux-related event (e.g.,
fertilization events, growing period), linear mixed models for randomized
complete block design were used with least significant difference tests at
P < 0.05 level. Differences in N2O and NO emissions due to main
effects like fertilizer treatment, year, treatment × year and block × treatment
as random effect were analyzed using linear mixed
models, and the model was fitted using the restricted maximum likelihood
procedure. Multiple linear or non-linear regression analysis was applied to
examine the correlations between N2O and NO fluxes and soil
environmental factors.
Results
Environmental variables
Annual precipitation was 804 mm from mid-September 2012 to the end of
September 2013, 890 mm from the beginning of October 2013 to mid-October
2014 (Fig. 1a); both values were smaller than the multiyear average
precipitation (914 mm). Apart from the precipitation, sprinkling irrigation
was applied four times per year depending on climatic conditions, amounting
to 150 and 135 mm for the 2 years, respectively. Soil temperature showed
comparable fluctuations with the air temperature, ranging from -0.1 to 28.3 ∘C.
The mean annual soil temperature was 14.9 and 14.6 ∘C for
the 2012/2013 and 2013/2014, respectively (Fig. 1a), with
no treatment impacts. Soil water content expressed as WFPS (water-filled
pore space) ranged from 20 to 80 % during the study period, which was
mainly influenced by rainfall and irrigation events. The mean WFPS values across
2012–2014 were 49.1, 49.7, and 48.6 % for TNN (no application of synthetic
nitrogen fertilizers or organic fertilizers), TUN, and TOM,
respectively, with no significant difference among them (Fig. 1b).
The temporal changes of (a) air and soil (5 cm)
temperatures, daily precipitation and irrigation, and (b) soil water content
expressed as WFPS (water-filled pore space) at a depth of 0–6 cm for all the
fertilizer treatments (i.e., the common practice with urea application
(TUN), the alternative practice with organic fertilizer application (TOM),
and no nitrogen fertilizer application (TNN)) in tea plantations during the
period from September 2012 to October 2014.
Soil NH4+ concentrations in TUN and TOM remarkably increased
following the fertilizer applications in March and October, and varied from
4.1 to 654 mg N kg-1SDW (soil dry weight) (Fig. 2a). The temporal
patterns of NO3- concentrations were also affected by nitrogen
applications, ranging from 2.4 to 188 mg N kg-1SDW, but the elevated
peaks were observed slightly later than the peaks for NH4+ (Fig. 2b),
reflecting the occurrence of nitrification. In contrast, both
NH4+ and NO3- concentrations in TNN were relatively
stable and always below 50 mg N kg-1SDW. Clearly, TUN and TOM
significantly enhanced soil mineral N concentrations, compared to TNN
(P < 0.05). During the study periods, soil NH4+ averaged
17, 138, and 113 mg N kg-1SDW for TNN, TUN, and TOM in the first year
(2012–2013), respectively; and mean NH4+ concentrations were 5.4,
172, and 106 mg N kg-1SDW for TNN, TUN, and TOM in the second year
(2013–2014), respectively (Fig. 2a). Compared to TUN, TOM greatly decreased
soil NH4+ concentrations during both studied years, although this
influence was not statistically significant for the first year. The mean
NO3- concentrations across 2012–2014 in TNN, TUN, and TOM were
around 5.7, 44, and 49 mg N kg-1SDW, respectively, with no significant
difference between TUN and TOM for either year (Fig. 2b).
Seasonal changes of the soil (a) ammonium (NH4+),
(b) nitrate (NO3-), and (c) dissolved organic carbon (DOC)
concentrations (mean ± standard error) for all the fertilizer
treatments ((i.e., the common practice with urea application (TUN), the
alternative practice with organic fertilizer application (TOM), and no
nitrogen fertilizer application (TNN)) in tea plantations during the period
from September 2012 to October 2014. SDW is the abbreviation of soil dry
weight.
Over the whole study period, soil DOC concentrations ranged from 17 to 317 mg C kg-1SDW
in TNN, from 10 to 488 mg C kg-1SDW in TUN, and from
20 to 559 mg C kg-1SDW in TOM (Fig. 2c). The mean DOC concentrations
across both the studied years were approximately 142, 146, and 179 mg C kg-1SDW
for TNN, TUN, and TOM, respectively. Obviously, TOM
significantly increased mean soil DOC concentration compared to TNN and TUN
(P < 0.05), but there was no significant difference between TUN and
TNN.
Annual N2O and NO fluxes and their direct
emission factors
The seasonal pattern of N2O fluxes was generally driven by temporal
variation in air and soil temperatures, which was relatively high during
the tea-growing season from March to September compared to winter. The
cumulative N2O release from all treatments across the tea-growing
season accounted for 54–86 % of the annual emission. Meanwhile, the
seasonal variability of N2O fluxes was also influenced by
fertilization and rainfall/irrigation events (Fig. 3a). The N2O fluxes
in TUN and TOM increased after each of the fertilizer applications, and then
gradually decreased to the levels comparable to those from TNN. Obviously,
the N2O emissions varied significantly with fertilizer treatment and
year. Across the investigated 2 years, annual N2O emissions ranged
from 1.9 kg N ha-1 yr-1 for TNN to 32.7 kg N ha-1 yr-1
for TOM (Table 2). Compared to TNN, the 2-year mean N2O emissions were
remarkably increased by 345 and 660 % for TUN and TOM, respectively
(P < 0.05). In comparison with TUN, TOM significantly increased
annual N2O emission by 71 % on average (P < 0.05). On the
annual scale, the direct emission factors of N2O were an average of
3.1 and 5.9 % for tea plantations under urea and organic fertilizer
treatment, respectively.
Seasonal changes of (a) nitrous oxide (N2O), and
(b) nitric oxide (NO) fluxes (mean ± standard error) for all the
fertilizer treatments ((i.e., the common practice with urea application
(TUN), the alternative practice with organic fertilizer application (TOM),
and no nitrogen fertilizer application (TNN)) in tea plantations during the
period from September 2012 to October 2014. The downward arrows denote the
time of fertilization.
Annual cumulative emissions of nitrous oxide (N2O, in
kg N ha-1 yr-1), nitric oxide (NO, in kg N ha-1 yr-1), and
N2O plus NO (in kg N ha-1 yr-1) as well as their respective
direct emission factors (EFd, in %) for tea
plantations under different fertilizer treatments during the period of
2012–2014.
Year
Treatmentb
N2Oc
EFd-N2O
NOc
EFd-NO
N2O+NOc
EFd-N2O+NO
2012–2013
TNN
6.2 ± 0.3a
2.8 ± 0.5a
9.0 ± 0.4a
TUN
21.1 ± 2.5b
3.3 ± 0.5
19.4 ± 0.3b
3.7 ± 0.1
40.6 ± 2.6b
7.0 ± 0.6
TOM
32.7 ± 0.7c
5.9 ± 0.2
17.0 ± 0.4c
3.2 ± 0.1
49.8 ± 1.0c
9.1 ± 0.2
2013–2014
TNN
1.9 ± 0.1a
0.4 ± 0.1a
2.3 ± 0.2a
TUN
14.4 ± 2.6b
2.8 ± 0.6
18.3 ± 0.5b
4.0 ± 0.1
32.8 ± 2.2b
6.8 ± 0.5
TOM
28.1 ± 1.3c
5.8 ± 0.3
12.3 ± 1.1c
2.7 ± 0.3
40.5 ± 2.3c
8.5 ± 0.5
2012–2014a
TNN
4.0 ± 0.1a
1.6 ± 0.2a
5.6 ± 0.2a
TUN
17.8 ± 2.5b
3.1 ± 0.6
18.9 ± 0.4b
3.8 ± 0.1
36.7 ± 2.4b
6.9 ± 0.5
TOM
30.4 ± 0.9c
5.9 ± 0.2
14.7 ± 0.6c
2.9 ± 0.1
45.1 ± 1.4c
8.8 ± 0.3
Data shown are means ± standard errors of four spatial replicates.
a Mean values of the 2 investigated years. b TNN, no nitrogen
fertilizer application; TUN, the common practice with urea application rate
of 450 kg N ha-1 yr-1; and TOM, the alternative practice with
organic fertilizer application rate of 450 kg N ha-1 yr-1.
c Different letters within the same column indicate significant
differences among treatments in each year at P < 0.05 level.
Clearly, the NO fluxes demonstrated a seasonal variability that was similar
to the N2O fluxes; that is, they were higher from March to September
and lower from December to March, and also affected by fertilization and
rainfall/irrigation events (Fig. 3b). Similar to N2O, the NO emissions
were greatly influenced by fertilizer treatment and year. The annual NO
emissions from all treatments ranged from 0.4 to 19.4 kg N ha-1 yr-1
(Table 2), of which 53–77 % was released during the tea-growing
season. Compared to TNN, the fertilizer applications (TUN and TOM)
significantly increased annual NO emission by 8–11 times on average
(P < 0.05). In contrast to N2O, TOM significantly decreased
annual NO emission by 22 % relative to TUN (P < 0.05). Averaging
across the 2 years, the direct emission factors of NO were 3.8 and
2.9 % for TUN and TOM, respectively. In addition, the N2O+NO
emissions were, on average, 5.6, 36.7, and 45.1 kg N ha-1 yr-1 for
TNN, TUN, and TOM, respectively, indicating that alternative organic
fertilization significantly enhanced nitrogen oxide emissions (Table 2).
Relationships of N2O and NO fluxes with soil
environmental factors
Across the 2-year study period, stepwise multiple regression analysis showed
that WFPS was the key factor controlling N2O and NO fluxes for both TUN
and TOM. Furthermore, a non-linear response curve best described the
decreases in molar ratios of NO to N2O fluxes with increasing WFPS
(Fig. 4). However, variations in WFPS could explain only 22–30 % of the
variance in the ratios, suggesting the importance of some other factors
(e.g., soil mineral N and temperature) on regulating these fluxes. To better
evaluate the combined effects of soil environmental factors on N2O and
NO fluxes, therefore, the revised “hole-in-the-pipe” model as described by
Yao et al. (2015) and Yan et al. (2015) was tested in this study. Over the
entire study period, the analysis results displayed that the temporal
variations of N2O and NO fluxes in TUN and TOM could be well described
by a combination of soil environmental factors, including soil mineral N,
WFPS, and temperature; that is, for TUN: Ln(N2O+NO)= 0.30Ln(NH4++NO3-)+2.53Ln(WFPS)
-13.9RTK,
R2= 0.97, P < 0.01; and Ln(N2O+NO)
= 0.17Ln
(NH4++NO3-)+2.68Ln(WFPS)-13.6RTK, R2= 0.96,
P < 0.01 for TOM; in which R and TK are the molar gas constant
(8.31 J mol-1 k-1) and soil temperature in Kelvin, respectively.
Effect of soil water content (expressed as WFPS,
water-filled pore space) on the molar ratios of nitric oxide (NO) to nitrous
oxide (N2O) fluxes in the fertilized treatments (i.e., the common
practice with urea application (TUN), and the alternative practice with
organic fertilizer application (TOM)) across the 2-year study period.
Discussion
Intra- and inter-annual variations of N2O and
NO fluxes and related environmental factors
Currently, the existing studies on tea fields are only focused on N2O
fluxes (Jumadi et al., 2005; Akiyama et al., 2006; Gogoi and Baruah, 2011;
Fu et al., 2012; Han et al., 2013a; Yamamoto et al., 2014), and therefore
they are not directly comparable to our present study. Our results
demonstrated annual characteristics of N2O and NO fluxes
simultaneously, which is important for a better understanding of how
climatic and environmental factors affect soil nitrogen turnover
processes in tea plantations. Generally, the subtropical climate is
characterized by the hot-humid season from April through September and the
cool-dry season from October through March every year, leading to
significant seasonal variations in soil environmental factors (Lin et al.,
2010). Driven by the seasonality of soil temperature, WFPS, NH4+,
and NO3- contents, the N2O and NO fluxes showed large
temporal variations (Skiba et al., 1998; Williams et al., 1999; Yan et al.,
2015) which were significantly higher during the tea-growing season
than in winter in this study (Fig. 3). The present result is in agreement
with previous studies conducted in other agricultural systems under the
subtropical climate, such as in vegetable fields (Min et al., 2012; Yao et
al., 2015), paddy rice–upland crop rotation ecosystems (Yao et al., 2013),
and orchard plantations (Lin et al., 2010), highlighting the climatic
controls on N2O and NO fluxes. Furthermore, up to 97 % of the
variance in N2O and NO fluxes could be explained by the combined
effects of soil temperature, WFPS, and mineral N content, indicating an
essential role of environmental factors on N2O and NO fluxes.
Overall, the knowledge of temporal variations in N2O and NO fluxes and
their related driving forces plays an important role for upscaling
nitrogenous gas fluxes to the regional and global scale.
On the other hand, our study clearly demonstrated that annual N2O and
NO emissions were significantly affected by the factor of year (Fig. 3),
even though the field management and soil temperature were comparable across
the 2 study years. A presumable reason for the pronounced inter-annual
variations of N2O and NO fluxes was the difference in precipitation,
particularly rainfall distribution throughout a year. For example, the
cumulative rainfall of 94 mm over a period from 20 to 26 June,
2013 was received that brought soil water content changing from 25 to
64 % WFPS on average (Fig. 1). As was also observed by our auxiliary
measurements that soil NH4+ and NO3- increased after
rainfall events during this period (Fig. 2a–b), the drying–rewetting event
could enhance the availability of nitrogen substrate and stimulate microbial
activity (Davidson, 1992; Williams et al., 1992; Yao et al., 2010b), and
thus, resulting in the following elevated fluxes of N2O and NO (Fig. 3a–b). Similarly, a number of studies also reported that the large
inter-annual variability in N2O and NO fluxes was mainly influenced by
the difference in annual distribution of the precipitation (e.g., Akiyama
and Tsuruta, 2003b; Yao et al., 2013).
Fertilizer type influencing annual N2O and NO
emissions
As tea plantations displayed high N2O production activities, they might
be a major source of nitrogenous gases in agricultural systems (Tokuda and
Hayatsu, 2001, 2004; Zhu et al., 2014). Our observations confirmed earlier
findings, with annual N2O emissions ranging from 14.4 to
32.7 kg N ha-1 yr-1 and NO emissions from 12.3 to 19.4 kg N ha-1 yr-1
for the fertilized tea plantations (Table 2). Generally, our
annual N2O emissions were within the range of the reported magnitudes
of 4.3–30.9 kg N ha-1 yr-1 for Chinese subtropical tea fields (Fu
et al., 2012; Han et al., 2013a). Based on the thorough review of
Akiyama et al. (2006), annual N2O emissions were presented
from 0.6 to 61.0 kg N ha-1 yr-1 for Japanese tea plantations, with a mean value of 24.3
kg N ha-1 yr-1. Obviously, the mean annual N2O emission in
our study (mean: 24.1 ± 4.0 kg N ha-1 yr-1) was well
consistent with the Japanese estimated value. In contrast, the magnitude of
N2O emissions from the present tea plantations was much higher than
that from the paddy rice–fallow cropping systems in the same region (0.8–6.6 kg N ha-1 yr-1,
Yao et al., 2014). With respect to NO, this is the
first time reporting annual NO emission for tea plantations to our
knowledge. On average, tea plantations released at least 16.8 kg N ha-1 yr-1
NO into the atmosphere, which fell within the range of 1.1–47.1 kg N ha-1 yr-1
for Chinese conventional vegetable fields under the
subtropical climate (e.g., Li and Wang, 2007; Mei et al., 2009; Deng et al.,
2012; Yao et al., 2015). As these authors acknowledged, their high NO
emissions for vegetable fields were mainly attributed to quite high nitrogen
inputs, ranging from 317 to 1464 kg N ha-1 yr-1. Nevertheless, our
observed annual NO emissions were relatively high compared to these
estimates of 0.5–6.5 kg N ha-1 yr-1 for rice–wheat cropping
systems with nitrogen application rates of 150–375 kg N ha-1 yr-1
(Zheng et al., 2003; Yao et al., 2013; Zhao et al., 2015) and of 4.0–6.9 kg N ha-1 yr-1 for forest ecosystems (Li et al., 2007) in Chinese
subtropical regions.
Although the fertilized tea plantations emitted large amounts of N2O
and NO, the magnitude of these emissions was significantly influenced by the
applied fertilizer type; that is, organically fertilized tea plantation
increased N2O emission by 71 % but decreased NO emission by 22 %,
compared to conventional urea application (Table 2). Our stimulatory effect
of organic fertilization on N2O emission and simultaneously inhibitory
impact on NO emission supports the findings of some previous studies
(Thornton et al., 1998; Akiyama and Tsuruta, 2003a, b; Hayakawa et al.,
2009). However, other studies showed that organic fertilization may reduce
N2O emissions or that emissions of N2O and NO were not affected at
all (Harrison et al., 1995; Akiyama and Tsuruta, 2003b; Vallejo et al.,
2006; Yao et al., 2009). It was generally accepted that the NO to N2O
emission ratio was used as a potential indicator for distinguishing between
nitrification and denitrification processes (Anderson and Levine, 1986; Skiba
et al., 1992; Harrison et al., 1995; Williams et al., 1998). As calculated
from the results of Table 2, the molar ratios of NO to N2O emissions
were in the range of 1.8–2.5 for the TUN plots but < 1.0 in the TOM
plots. This may indicate that nitrification was probably the dominant
process for N2O and NO production in the conventional urea treatment,
while denitrification would be more dominant process in organic
fertilization, although both nitrification and denitrification could occur
under the present soil moisture conditions (i.e., 20–80 %WFPS)
according to a conceptual model proposed by Davidson (1991). Denitrifiers
have a very high affinity for NO and tend to utilize it in preference to
N2O as a substrate even in well-aerated soils (Conrad, 2002; Yamulki
and Jarvis, 2002). The differences in N2O and NO emission response between urea and organic fertilizer
treatment are therefore to be expected. This view was further supported by our observations of soil
NH4+ and DOC. It is well recognized that NH4+ enhanced
NO fluxes since it affected nitrification, whereas the addition of DOC
generally diminished these fluxes by enhancing soil respiration and thereby
inducing the anaerobic conditions that favored the production of N2O
and the consumption of NO through denitrification (Granli and Bockman, 1994;
Vallejo et al., 2006; Meijide et al., 2007). In this study, therefore, TOM
with lower NH4+ and higher DOC, emitted more N2O and less NO
than in TUN. Alternatively, opposite trends observed for N2O and
NO emissions between TUN and TOM were probably regulated by soil
heterotrophic nitrification, the direct oxidation of organic N to
NO3- without passing through mineralization (Müller et al.,
2004; Islam et al., 2007). It has been identified that heterotrophic
nitrification, especially for acidic soils with organic amendments, plays an
important role in soil nitrogen transformations, including the production
and consumption processes of NH4+ and NO3- as well as
N2O and NO (Dunfield and Knowles, 1998; Zhu et al., 2011, 2014;
Medinets et al., 2015). Hence, one can assume that given WFPS being
comparable in all treatments, heterotrophic nitrification was the most
important process for consumption of NO and production of N2O in the
organic fertilizer treatment, whereas autotrophic nitrification dominated in
urea application. Besides, it has been validated that soils receiving
organic amendments significantly reduce NO fluxes as a result of increased
NO consumption via aerobic co-oxidation reactions in heterotrophic bacteria
(Baumgärtner et al., 1996; Dunfield and Knowles, 1998; Conrad, 2002).
This assumption could be also supported by our measurements of soil
NH4+ and NO3-; that is, TOM showed comparable, even
slightly higher, NO3- relative to TUN, although TUN demonstrated
relatively high NH4+ due to the rapid release of urea hydrolysis
(Fig. 2a-b). This indicated that heterotrophic nitrification contributed
substantially to the production of NO3- in TOM, because the
application of organic matter can enhance the direct oxidation of organic N
to NO3- via soil heterotrophic nitrification (Zhu et al., 2011,
2014). Overall, although our data supported the above mentioned views, the
exact reaction mechanisms were not determined directly in the present study.
Therefore, further detailed investigations are needed to provide a complete
assessment on the relative contribution of autotrophic nitrification,
heterotrophic nitrification and denitrification to N2O and NO fluxes
from tea plantations, based on new approaches and techniques, e.g., 15N
tracing techniques (Müller et al., 2007).
Background N2O and NO emissions and direct
emission factors of fertilizer N
Although background N2O and NO emissions occurring in the zero-N
control have been recognized as a major component for developing a national
emission inventory of nitrogenous gases (Zheng et al., 2004; Huang and Li,
2014), direct measurements of background emissions, especially measurements
covering an entire year for tea plantations, have been rare (Akiyama et al.,
2006). In our study, the mean annual background emissions were
4.0 kg N ha-1 yr-1 for N2O and at least 1.6 kg N ha-1 yr-1
for NO, respectively (Table 2). Our background N2O emission is
comparable to the preliminary estimate of 3.66–4.24 kg N ha-1 yr-1
for Japanese tea fields (Akiyama et al., 2006), but it is relatively low,
compared to the reported value of 7.1 kg N ha-1 yr-1 for another tea
field in the Chinese subtropical region (Fu et al., 2012). Nevertheless,
these background N2O emissions revealed by present and previous studies
in tea plantations are generally higher than those estimates for cereal
grain croplands (ranging from 0.1 to 3.67 kg N ha-1 yr-1, with a
mean of 1.35 kg N ha-1 yr-1, Gu et al., 2007) and vegetable fields
(1.1–2.7 kg N ha-1 yr-1, Wang et al., 2011; Liu et al., 2013) in
China, or the recommended default value of 1 kg N ha-1 yr-1 by
IPCC (IPCC, 2006). Similarly, our mean background NO emission from tea
plantations is greater, relative to cereal grain croplands (0.2–0.9 kg N ha-1 yr-1, Yao et al., 2013; Yan et al., 2015) and vegetable
fields (0.2–0.8 kg N ha-1 yr-1, Yao et al., 2015) in China. These
comparisons highlight the characteristic of high background N2O and NO
emissions from tea plantations, which is probably due to long-term heavy
nitrogen fertilization and subsequent soil acidification (Tokuda and
Hayatsu, 2004; Yamamoto et al., 2014). Soil acidity appears to be an
important factor in affecting biotic and abiotic processes and consequently
promoting nitrogen losses, such as enhancing N2O production ratios from
nitrification and depressing the conversion of N2O to N2 in
denitrification (Zhu et al., 2011) as well as inducing chemodenitrification
for NO production (Venterea et al., 2003; Medinets et al., 2015). It should,
however, be noted that with limited data available from tea plantations of
the world and consequently the high uncertainties of meta-analytic results,
caution should be exercised in the interpretation of the differences in
background emissions of N2O and NO between the current and previous
studies.
In this study, the mean annual emission factor of NO for TUN was 3.8 %,
which was substantially higher than that estimated for Chinese rice fields
(0.04 %) and uplands (0.67 %) (Huang and Li, 2014), or the average value
of 0.7 % for global upland croplands (Bouwman et al., 2002; Yan et al.,
2005). The NO emissions from TUN were greatly reduced by practicing TOM,
giving an emission factor of 2.9 % (Table 2). Although the NO emission
factors were lower for TOM relative to TUN, TOM could not be proposed as a
preferred management option for tea plantations because it emitted much
higher N2O or N2O+NO. The N2O emission factors obtained on
this study site (i.e., 3.1 % for TUN and 5.9 % for TOM) were
considerably higher than those estimated for Japanese tea fields (2.8 %,
Akiyama et al., 2006) and another Chinese subtropical tea field
(1.9–2.2 %, Fu et al., 2012), or the IPCC default value of 1 % for
global upland croplands (IPCC, 2006). These results corroborated the
assertion that tea plantations are an important source of atmospheric
N2O in tropical and subtropical regions, and furthermore they extended
the earlier findings by demonstrating the characteristic of high NO and
N2O+NO emissions from tea plantations.
It is noteworthy that although our investigated tea plantations represent
the major and typical tea-planting types in Chinese subtropical regions, the
obtained background and direct emission factors of N2O and NO could not
be simply extrapolated to a regional scale due to the limited site results
(e.g., only four chamber-spatial measurements for each treatment) and the
characteristics of high spatial variability of nitrogenous gas fluxes
(e.g., Li et al., 2013). A more holistic approach for regional estimates of
N2O and NO emissions from tea plantations should be based on
meta-analysis of published nitrogenous gas fluxes to obtain representative
background and direct emission factors or on the basis of biogeochemical
modeling validated by regional field data; these are methodologies
suggested by the IPCC (IPCC, 2006).
Conclusions
Based on 2-year field measurements, this study provided an integrated
evaluation on N2O and NO emissions in response to no nitrogen
fertilization, conventional urea, and alternative oilcake application in
Chinese subtropical tea plantations. Clearly, both N2O and NO emissions
varied substantially within a year and between different years, which was
chiefly driven by the fertilization events and the distribution and size of
rain events. Soil water-filled pore space, temperature and mineral nitrogen
content appeared to be the major factors regulating the seasonality of
N2O and NO fluxes, and their correlation could be well presented by a
revised “hole-in-the-pipe” model. Compared to no nitrogen fertilization,
the application of urea and organic fertilizer to tea plantations stimulated
annual N2O and NO emissions. On average, the organic fertilizer-induced
emission factor of N2O (i.e., 5.9 %) was significantly higher than
the urea-induced emission factor of 3.1 %; however, the urea-induced
emission factor of NO (i.e., 3.8 %) was significantly higher than the
organic fertilizer-induced emission factor of 2.9 %. In total, the
substitution of conventional urea by organic fertilizer in tea plantations
significantly increased N2O+NO emissions, and this stimulation effect
should be taken into account in the design and evaluation of soil carbon
sequestration strategies of organic fertilization. Although the magnitude of
N2O and NO emissions was significantly influenced by the applied
fertilizer type, annual emission factors of N2O and NO induced by
either urea or organic fertilizer application were all substantially higher
than those defaults for global upland croplands, indicating that tea plantations
may contribute substantially to total N2O and NO emissions from
croplands in China. The results from this study, however, may not
necessarily indicate the most feasible fertilizer management option in the tea
plantations, as a result of only presenting two nitrogen-trace gas species
(i.e., N2O and NO). Therefore, when we finally provide a complete
evaluation of nitrogen fertilizer practice in tea plantations from an
integrated agronomic and environmental point of view, future field
measurements are necessary to include the climatically and environmentally
important carbon- and nitrogen-trace gas fluxes (i.e., CH4, CO2,
NO, N2O, and NH3) as well as plant qualities and yields.