Introduction
Soils store approximately 2500 Pg of carbon (including organic and inorganic
carbon) globally, equivalent to 3.3 and 4.5 times the carbon in the
atmosphere (760 Pg) and terrestrial plants (560 Pg), respectively (Lal,
2004). Slight variations in the soil carbon pool will hence severely
influence atmospheric CO2 concentrations and have important implications
for climate change (Davidson and Janssens, 2006; Trumbore and Czimczik,
2008). Respiration and leaching are two main processes responsible for soil
carbon loss. While respiration has received considerable research attention
(Raich and Schlesinger, 1992; Raich and Potter, 1995; Hoover et al., 2016;
Burri et al., 2015; Escolar et al., 2015), leaching is relatively poorly
constrained despite its importance in certain ecosystems (Cole et al.,
2007; Battin et al., 2008; Liu et al.,
2017). For instance, soil carbon leached from forests, grasslands, and
croplands is estimated to be 15.1, 32.4, and 20.5 g C m-2 yr-1
across Europe, representing 4, 14, and 8 % of net ecosystem exchange
(NEE), respectively (Kindler et al., 2011). Additionally, leaching of carbon
previously preserved in surface litter and soil layers is believed to be a
main source of dissolved organic and inorganic matter in inland waters
(Spencer et al., 2008). In particular, soil inorganic carbon (SIC) that
occurs widely in arid and semiarid regions is more prone to leaching than
organic carbon during sporadic high precipitation events (Lal and Kimble,
2000). Despite the importance of leaching loss in regional soil carbon
budgets, very little detailed data exists to investigate and compare the relative
contribution of respiration and leaching processes to soil carbon loss.
Climate change is reported to increase the frequency as well as the intensity of
extreme precipitation events (EPEs; Knapp et al., 2002; Goswami et al.,
2006; Parry et al., 2007; Min et al., 2011; Reichstein et al., 2013),
especially in arid regions (Donat et al., 2017). In northwestern China, the
frequency and intensity of EPEs have shown an increasing trend in the most
recent 50 years, constituting a much higher proportion of total
precipitation than light precipitation events (Liu et al., 2005; Chen et
al., 2012; Wang et al., 2012, 2014; Fu et al., 2013).
Increasing EPEs will not only enhance soil carbon leaching but also affect
soil respiration processes by increasing soluble substrates for
microbial decomposition and potentially inducing hypoxic conditions (Knapp
et al., 2002; Harper et al., 2005; Morel et al., 2009; Unger et al., 2010).
Hence, it is critical to evaluate the effects of EPEs on soil respiration
and leaching processes in order to better understand the impact of climate
change on terrestrial carbon cycling, especially in arid and semiarid
regions.
Grasslands, containing 20 % of the global soil carbon pool, are the most
widespread ecosystems in arid and semiarid regions globally (Jobbagy and
Jackson, 2000). The deposition rate of carbonate is relatively high in
grassland soils with a high alkalinity and aridity (Lal, 2008; Yang et al.,
2012), and hence SIC is the major form of soil carbon in many grasslands (Mi
et al., 2008). SIC storage in China is approximately 53.3–77.9 Pg (Li et
al., 2007; Mi et al., 2008), 54 % of which is mainly distributed in the
temperate and alpine grasslands located in Inner Mongolia and the Qinghai–Tibetan
Plateau (Mi et al., 2008). From the 1980s to 2000s, SIC in the topsoil of Chinese
grasslands was estimated to decrease by 26.8 g C m-2 yr-1,
mainly attributed to soil acidification (Yang et al., 2012). Alternatively,
precipitation is one of the main factors influencing the distribution and
storage of SIC in arid and semiarid regions (Batjes, 1998; Lal and Kimble,
2000). Mi et al. (2008) found that 84 % of SIC in China was distributed
in areas with a mean annual precipitation (MAP) of < 500 mm and
that SIC content decreased significantly with the increase in MAP. Given the
high leaching potential of SIC in grassland soils under altered precipitation
patterns in the future, we hypothesize that EPEs may significantly enhance
SIC loss through leaching processes and further reduce SIC storage in
grasslands.
In this study, soils were collected from varied depths of three typical
temperate and alpine grasslands in Inner Mongolia and the Qinghai–Tibetan Plateau
to construct soil columns for a laboratory incubation study. Using simulated
EPEs, we examined soil carbon loss through respiration and leaching processes
and compared their fluxes after EPEs. In addition, the leaf litter of a C4 grass
was added to the surface of one set of soil columns to compare soil carbon
loss from bare versus litter-covered soils and to estimate the contribution
of litter-derived carbon to soil respiration after EPEs. Our research
objectives were (1) to investigate the influence of EPEs on soil
respiration, (2) to quantify the loss of SIC and soil organic carbon (SOC)
through leaching during EPEs, and (3) to compare the relative importance of
respiration and leaching in EPE-induced soil carbon loss from grassland
soils.
Materials and methods
Study area
For the incubation experiment, soils were collected from three different
sites of temperate and alpine grasslands in China with varied environmental
characteristics. Temperate grasslands were sampled near Xilinhot (XLHT;
116∘22′ E, 44∘8′ N; mean elevation 1170 m) and Keqi
(KQ; 117∘15′ E, 43∘ 18′ N; mean elevation 1250 m)
within the arid and semiarid regions of Inner Mongolia (Fig. S1 in the
Supplement) with MAP of 299 and 402 mm and mean annual temperature (MAT) of
1.2 and 0.4 ∘C, respectively. Soil in this region is mainly chestnut
soil, classified as Calcic Chernozems according to the World Reference Base
for Soil Resources (Steffens et al., 2008; IUSS working group WRB, 2015),
with Stipa klemenzii, Stipa Goboca, Stipa breviflora, and Stipa glareosa as the dominating species (Sui and
Zhou, 2013). The alpine grassland was sampled in Gangcha (GC;
100∘7′ E, 37∘19′ N; mean elevation 3500 m) located
north of the Qinghai Lake on the northeastern edge of the Qinghai–Tibetan
Plateau. The GC site has a MAT of 0.4 ∘C, a MAP of 370 mm, and a
mean annual evaporation (MAE) of 607 mm. Soils at this site are mainly Gelic
Cambisol (IUSS working group WRB, 2015), with Potentilla ansrina Rosaceae, Elymus nutans Griseb, and Deyeuxia arundinacea
as the dominant species.
Soils were collected by digging soil pits of
25 cm × 25 cm × 70 cm from the temperate (XLHT and KQ)
and alpine (GC) sites in October 2014 and August 2015, respectively. At each
site, three plots (200 m × 200 m) were selected (>200 m in between) with three random soil pits (distance of ∼ 5 m in
between) sampled within each plot. Soils from the same depth (0–20, 20–40,
and 40–60 cm) of the three soil pits were mixed in situ for each plot,
shipped back to the laboratory immediately, and stored at 4 ∘C before the
experiment started within 1 month. As a result, each sampling site had
three “true” replicates from the field for the soil column experiment.
Design of the soil column experiment for monitoring soil respiration
and leaching after simulated extreme precipitation events (EPEs).
Bulk properties of soil samples collected from the temperate and
alpine grasslands for the soil column experiment (mean ± standard
error; n = 3).
Station
Depth
SOC
SIC
N
SOC : N
pH
δ13C
FWC
Max. WHC
BD
Clay
Silt
Sand
(cm)
(%)
(%)
(%)
ratio
(‰)
(%)
(%)
(g cm-3)
(%)
(%)
(%)
Xilinhot (XLHT)
0–20
1.48 ± 0.02
0.41 ± 0.01
0.18 ± 0.00
8.03 ± 0.18
8.98 ± 0.03
-24.1
10.65 ± 0.11
47.12 ± 0.37
1.06 ± 0.02
0.4
64.6
35.0
20–40
1.00 ± 0.05
0.64 ± 0.00
0.13 ± 0.00
7.69 ± 0.22
9.09 ± 0.01
-24.1
6.48 ± 0.24
44.92 ± 0.25
1.24 ± 0.05
0.5
58.2
41.3
40–60
0.67 ± 0.03
1.05 ± 0.01
0.09 ± 0.00
7.09 ± 0.22
9.09 ± 0.04
-23.7
5.56 ± 0.11
39.78 ± 0.39
1.31 ± 0.03
0.6
58.5
41.0
Keqi (KQ)
0–20
3.36 ± 0.05
0.02 ± 0.00
0.29 ± 0.00
11.48 ± 0.24
7.79 ± 0.10
-26.0
19.59 ± 0.22
65.57 ± 0.82
1.14 ± 0.03
0.4
41.0
58.6
20–40
2.52 ± 0.04
0.01 ± 0.00
0.22 ± 0.00
11.59 ± 0.27
7.63 ± 0.04
-25.9
8.56 ± 0.05
53.59 ± 1.98
1.22 ± 0.01
0.2
55.7
44.1
40–60
1.65 ± 0.03
0.02 ± 0.00
0.14 ± 0.00
11.49 ± 0.42
7.57 ± 0.12
-25.5
8.00 ± 0.27
42.92 ± 0.57
1.19 ± 0.01
0.2
61.6
38.1
Gangcha (GC)
0–20
3.32 ± 0.23
0.34 ± 0.04
0.31 ± 0.03
10.70 ± 1.28
8.53 ± 0.07
-26.3
33.24 ± 0.68
60.79 ± 0.21
n.d.
1.3
75.9
22.8
20–40
2.90 ± 0.18
0.44 ± 0.10
0.29 ± 0.01
9.93 ± 0.69
8.60 ± 0.03
-24.0
36.15 ± 0.52
62.03 ± 0.30
n.d.
0.9
75.8
23.3
40–60
2.12 ± 0.22
0.52 ± 0.06
0.20 ± 0.02
10.55 ± 1.50
8.76 ± 0.10
-25.3
35.79 ± 0.91
62.85 ± 0.61
n.d.
0.6
64.0
35.4
SOC: soil organic carbon; SIC: soil inorganic carbon; N: nitrogen; FWC: field
water content; Max. WHC: maximum water-holding capacity; BD: bulk density;
Clay: soil particle size < 0.2 µm; Silt: 0.2 µm
< soil particle size < 20 µm; Sand: soil particle
size > 20 µm; n.d.: not determined.
Soil column experiment and simulated EPEs
For the laboratory experiment, we reconstructed soil columns of similar
structures and texture under controlled conditions and used gravity to
collect soil leachates. This approach is commonly used in process-related
research (Hendry et al., 2001; Thaysen et al., 2014; Artiola and Walworth,
2009; Aslam et al., 2015) as it minimizes experimental errors and bias caused
by unknown factors including soil heterogeneity and microbial community
variations. It is also more favorable in terms of quantifying soil carbon
leaching loss as it circumvents pore-water contamination by vacuum suction in
the field. In particular, leachate sampling by gravity from soil columns
prevents alterations to DIC concentrations, which may be caused by CO2
outgassing using vacuum suction in field studies. Artificial soil columns
were constructed in the laboratory with polymethyl methacrylate frames
(diameter: 10 cm; height: 70 cm; Fig. 1). The bottom of each column had an
aperture (inner diameter: 0.6 cm; height: 3 cm) for the collection of soil
leachates, and the column top was fitted with an airtight lid connected to
two tubes for gas exchange and collection. Empty columns were soaked in
0.1 mM hydrochloric acid (HCl) solutions for 12 h and rinsed with distilled
water before use. Column bottoms were packed with pre-cleaned quartz sand
(5 cm thick; soaked in 0.1 mM HCl and combusted at 450 ∘C for 6 h
before use) with a layer of nylon net (pore size: 150 µm; diameter:
10 cm) on both sides to prevent the movement of soil particles.
Subsequently, soils were passed through 2 mm sieves with roots removed and
packed into each column at the corresponding depths (in the sequence of
40-60, 20-40, and 0-20 cm). Soils were compacted gently to maintain a
similar bulk density as in the field (Table 1). The water content of each soil
layer was separately adjusted to 60 % of the maximum water-holding
capacity (Table 1) to provide an ideal moisture condition for microbial
growth (Howard and Howard, 1993; Rey et al., 2005). There was a 10 cm
headspace unfilled with soil for each column.
Six soil columns (one litter-amended and one non-amended column for each of
the three sampling plots) were set up for each site as described above and
pre-incubated for 2 weeks in the laboratory to allow for the recovery of
microbial communities after disturbance. Subsequently, the leaf litter of a C4
grass, Cleistogenes squarrosa, a dominant species in the grasslands
of northern China (Tian et al., 2015), was added to the surface of three
columns in an amount equivalent to the aboveground biomass in the field
(1.26 g for the XLHT and KQ sites and 1.59 g for the GC site; Bai et al.,
2008). The isotopic signal of the leaf litter (δ13C of
-16.2 ‰) allowed us to estimate the contribution of
litter-derived CO2 to total soil respiration. The columns were
pre-incubated again for 7 days. The basal respiration rate was measured by
collecting CO2 gas in the column headspace after 4 h of incubation.
Temperature was recorded every day during the whole incubation period
(23 ± 1 ∘C).
According to historical precipitation records (Fig. S2), more than 70 %
of the annual precipitation occurs from June to August in the study area,
mainly in the form of two to four heavy precipitation events. Therefore, a total of
three EPEs were simulated over a period of 2 months for each soil using
artificial rainwater prepared according to the rainwater composition at the
corresponding sites (pH of 7.3; Table S1 in the Supplement; Tang et al.,
2014; Zhang et al., 2013). A maximum rainfall intensity of ∼ 100 mm
per precipitation event has been recorded in the past 2 decades in the
study area (Fig. S2) and is predicted to increase by 18.1 % in the late
21st century in north China (Chen et al., 2012). Hence, approximately 1 L of
rainwater (rainfall of ∼ 127 mm), comparable to 30 % of the MAP of
the investigated sites, was added to the surface of each soil column over
3–4 h at rates of one drop per second using syringes and allowed to leach
through the column to be collected with a clean beaker within 12–14 h. The
leachates were weighed, filtered through a 0.45 µm PTFE syringe
filter, and analyzed for dissolved organic carbon (DOC) and dissolved
inorganic carbon (DIC) concentrations immediately. To monitor soil
respiration every 1–2 days following each EPE, soil columns were first
aerated for 1 h using CO2-depleted air that had been passed through
saturated sodium hydroxide (NaOH) solutions (twice; Fig. 1) and then
incubated for 4 h with lids closed. CO2 gas in the column headspace was
collected by gastight syringes for the subsequent measurement. After
the collection of CO2 gas, the lids were open to allow for exchange with the
ambient air. Soil respiration was monitored for 30 days after the first EPE
and observed to stabilize approximately on the 20th day (Fig. S3). Hence, the
first, second, and third EPEs were conducted on the 1st, 31st, and 51st day
of incubation, and the CO2 measurement was conducted for approximately
30, 20, and 20 days after the first, second, and third EPEs, respectively.
Basal respiration was considered to be represented by the stabilized
respiration rate at the end of each EPE cycle. In addition, due to
constrained time and logistic reasons, the soil respiration after the second
EPE in the KQ soils was not monitored, and the cumulative respiration after
the second EPE was calculated as the average respiration after the first and
third EPEs in the KQ soils.
Sample analyses
Soil pH was measured at a soil : water ratio of 1:2.5 (w:v) using a pH
meter (Sartorius PB-10). Soil texture was examined by laser diffraction using
a Malvern Mastersizer 2000 (Malvern Instruments Ltd., UK) after the removal of
organic matter and calcium carbonates. Soil field water content was
determined by the difference between moist and dried soils (dried at
105 ∘C for 8 h). Maximum water-holding capacity was estimated by
weighing soils before and after the removal of redundant water from fully soaked
soils (in water for 8 h). For SOC analysis, dried soils were decarbonated by
exposure to concentrated HCl vapor for 72 h, followed by saturated NaOH
solutions for 48 h to neutralize extra HCl, and then dried at
45 ∘C. Total soil carbon, SOC (after decarbonation), and nitrogen (N)
contents were measured by combustion using an elemental analyzer (Vario EL
III; Elementar, Hanau, Germany). SIC was calculated as the difference between
total carbon and SOC contents. Small aliquots of the soil leachates were
analyzed immediately on a Multi N / C 3100-TOC/TN Analyzer (Analytik
Jena, Germany) for DIC and DOC concentrations (with the latter acidified to
pH < 2 with concentrated HCl before analysis). It should be
mentioned that the DIC concentration may vary due to exchanges between
dissolved and atmospheric CO2 during leachate collection. However,
the potential contribution from this process was < 7 % owing to the
low proportions of dissolved CO2 in total DIC of our samples (Table S2)
as calculated according to Ran et al. (2015). CO2 concentration in the
soil column headspace was determined by a gas chromatograph (Agilent 7890A,
USA) coupled with a flame ionization detector (FID).
To examine the contribution of SOC- and litter-derived carbon to soil
respiration, the δ13C values of SOC and CO2 gas were
determined on an isotope ratio mass spectrometer (Deltaplus XP; Thermo,
Germany) with a precision of ±0.2 ‰. To estimate the
contribution of SOC degradation to leached DIC, the δ13C values of
DIC were determined on a Picarro isotopic CO2 analyzer equipped with an
automated DIC sample preparation system (AutoMate) based on a wavelength-scanned cavity ring-down spectroscopy technique (Picarro AM-CRDS, USA). The
precision for the DIC-δ13C measurement was ±0.3 ‰. Due
to budget constraints and logistic reasons, we only measured the
δ13C of the respired CO2 in the GC soils during the first EPE
and the leached DIC in the XLHT soils.
Data analysis and statistics
The relative contribution of litter- and SOC-derived CO2 to total
respired CO2 in the litter-amended soils was estimated using the
following mass balance model:
flitter-derived+fSOC-derived=1,flitter-derived×δ13Clitter-derived+fSOC-derived×δ13CSOC-derived=δ13Crespired-CO2,
where flitter-derived and fSOC-derived are the proportion
of litter- and SOC-derived CO2 in the total respired CO2; δ13Clitter-derived is the δ13C value of litter-derived
CO2, equivalent to -16.25 ‰;
δ13CSOC-derived is the δ13C value of
SOC-derived CO2, which assumes the same value as that in the non-amended
soils at the beginning of incubation (-23.1 ‰) according to
Cerling et al. (1991); and δ13Crespired-CO2 is the
measured δ13C of respired CO2.
Similarly, the relative contribution of lithogenic carbonate and biogenic
DIC derived from SOC degradation to leached DIC was assessed according to
the following isotopic mass balance model:
fcarbonate+fbiogenic-DIC=1,fcarbonate×δ13Ccarbonate+fbiogenic-DIC×δ13Cbiogenic-DIC=δ13CDIC,
where fcarbonate and fbiogenic-DIC are the proportion of
carbonate and biogenic DIC in total DIC; δ13Ccarbonate
is the δ13C value of soil carbonate, equivalent to 0 ‰
(Edwards and Saltzman, 2016); and δ13Cbiogenic-DIC is the
δ13C value of biogenic carbonate and bicarbonate derived from the
dissolution of CO2 produced by SOC degradation, which is estimated to
shift by approximately 8 ‰ compared with the δ13C value
of soil-respired CO2 (-24 ‰ here) due to isotope
fractionation during CO2 dissolution (Zhang et al., 1995). Hence,
δ13Cbiogenic-DIC is estimated to be -16 ‰.
The δ13CDIC value is the measured δ13C signature of
leached DIC. The isotopic fractionation of leached DIC due to CO2 loss in an
open system is insignificant when the partial pressure of CO2
(pCO2) in the solution is lower than twice that of the surrounding
atmosphere (Hendy, 1971; Doctor et al., 2008). In the present study,
pCO2 in the XLHT leachates was low (∼ 400 µatm
assuming alkalinity equals to DIC concentration; Table S2) due to its high
pH, low soil respiration, and dilution of dissolved CO2 under an EPE. Thus,
we considered the influence of CO2 outgassing on the δ13C of
leached DIC to be negligible.
EPE-induced CO2 release via respiration was assessed following two
steps. First, cumulative respiration during the first 20 days after each EPE
(until respiration rate stabilized) was calculated. Second, the difference
between the measured cumulative respiration and that estimated using the
stabilized basal respiration rate after each EPE was calculated as the
EPE-induced CO2 release.
Independent sample T tests (group size = 2) and one-way ANOVA analysis
(group size > 2) were used to compare the dissolved carbon
concentrations and fluxes among different columns. Linear regression analysis
was used to assess correlations between leachate carbon flux and influencing
factors (carbon content, soil pH, soil texture, etc.). All these analyses
were performed using IBM SPSS Statistics 22. Differences and correlations
are considered to be significant at a level of p < 0.05.
Results and discussion
Bulk properties of grassland soil samples
In the investigated grassland soils, SOC represented 59–99 % of soil
carbon and exhibited δ13C values typical of C3 plant inputs
(ranging from -24.1 to -26.3 ‰; Table 1). The XLHT soil had
much lower SOC and nitrogen (N) contents than the KQ and GC soils despite a
similar soil texture (p < 0.05; Table 1). The SOC : N ratio was
also lowest in XLHT (7.09–8.03), indicating a more decomposed state of soil
organic matter (Weiss et al., 2016). Conversely, the SIC content was highest
in XLHT and lowest in KQ, in line with soil pH variations at these sites,
i.e., lowest pH in KQ and highest in XLHT. This correlation of SIC with soil
pH is consistent with the results of Shi et al. (2012), showing that pH is
the most important factor controlling SIC variation across the Mongolian and
Tibetan grasslands. In terms of depth variations, soils became coarser with
depth in XLHT and GC, but became finer with increasing depth in KQ. The SOC
and N contents decreased with depth in all soils due to declining plant
inputs (p < 0.05; Table 1), while the SOC : N ratio remained
relatively similar (except a small decrease with depth in XLHT). By contrast,
XLHT and GC soils showed an increasing SIC content with depth
(p < 0.05; Table 1) because SIC, with a good solubility, is
prone to leaching from the topsoil and subsequently precipitates in the
deeper soil (Mi et al., 2008; Tan et al., 2014). The KQ soil, showing an
almost neutral pH, had an invariant SIC content and pH with depth. Overall,
the varied properties (including SOC, SIC, pH, etc.) of these soils allowed
us to compare the effects of EPEs on soil respiration and leaching processes
in different grassland soils.
EPE-induced changes to soil respiration
Shortly after each simulated EPE, soil respiration was similar to or lower
than basal respiration (Fig. S3). The latter case may be attributed to
hypoxic conditions induced by water saturation during EPEs (Hartnett and
Devol, 2003; Jessen et al., 2017). Subsequently, soil respiration increased
and peaked after approximately 1 week due to the recovery of microbial
activity with improved soil aeration (Borken and Matzner, 2009). It then
decreased to a constant level approximately 20 days after each EPE (Fig. S3).
The transient increase in respiration was consistent with the “Birch
effect” (Birch, 1964), i.e., a pulse of soil respiration after rewetting
events due to resuscitation of microorganisms and improved diffusive
transport of substrate and extracellular enzymes (Borken and Matzner, 2009;
Navarro-García et al., 2012; Placella et al., 2012). The maximum soil
respiration rates were 40.6 and 37.3 mg C m-2 h-1 after EPEs in
the non-amended KQ and GC soils, respectively. These rates were significantly
higher than in the XLHT soil (13.7 mg C m-2 h-1), likely
related to the higher SOC content in the former soils. The maximum specific
soil respiration rates normalized to SOC were 2.2, 2.6, and
2.0 µg C g-1 SOC h-1 in the non-amended GC, KQ, and
XLHT soils, respectively. Therefore, SOC degradability was quite similar in
the alpine and temperate grassland soils.
The δ13C values of respired CO2 in the litter-amended
Gangcha (GC) soils after the first extreme precipitation event (EPE). Mean
values are shown with standard error (n=3).
Total (a) and specific (b) EPE-induced CO2 release in the litter-amended and non-amended
grassland soils during three EPEs. Mean values are shown with standard
deviation (n=3). Lowercase letters (a, b, c) indicate
significantly different levels among the litter-amended and non-amended soils
determined by Duncan's multiple range test (one-way ANOVA,
p < 0.05).
Total respired CO2 was higher in the litter-amended than non-amended
soils before and after EPEs (Fig. S6). The cumulative respired CO2 amounts in
the litter-amended XLHT, KQ, and GC soils were 16.7, 54.8, and
44.6 g C m-2 during three EPEs, which is 20, 22, and 15 % higher than
the non-amended soils, respectively. Due to the wide presence of litter
coverage in our studied soils, the litter effect on soil respiration should be
considered when estimating carbon budgets for these grassland soils. The
higher total respired CO2 in litter-amended soils might be caused by one
or both of the following: (1) the degradation of labile components in the
fresh litter and/or (2) induced priming effects due to the addition of an easily
available energy source (Fröberg et al., 2005; Ahmad et al., 2013). To
distinguish the influences of the above two factors on total respired CO2
and further differentiate the contribution of litter (C4) and SOC (C3) to the
respired CO2, we examined the δ13C values of CO2 evolved
from the GC soils after the first EPE. On the first day after EPE, CO2
from the non-amended and litter-amended GC soils had a δ13C value
of -23.1 and -18.7 ‰, respectively. The latter was close to the
δ13C signature of the added litter (-16.25 ‰). Using the
two-endmember mixing model of Eqs. (1) and (2), we calculated that litter
contributed ∼ 64 % of the respired CO2 in the litter-amended
GC soils. However, along with the consumption of labile carbon in litter, the
δ13C signature of CO2 decreased from -18.7 ‰ on
day 1 to -21.8 ‰ on day 25 after an EPE in the litter-amended soils
(Fig. 2). Accordingly, the proportion of litter-derived CO2 decreased
from 64 to 20 %. The litter-derived CO2 flux in litter-amended GC
soils was estimated to range from 7.0 to 17.5 mg C m-2 h-1,
while the SOC-derived CO2 flux increased from 6.2 to
15.7 mg C m-2 h-1 after the first EPE (Fig. S4). Compared with
the SOC-derived CO2 flux in non-amended GC soils (ranging from 17.2 to
27.1 mg C m-2 h-1), litter addition had a negative priming
effect on the degradation of native SOC while increasing total respiration
through labile litter degradation.
Using the data shown in Figs. S3 and S5, we calculated that total EPE-induced
CO2 release during three EPEs was higher in the KQ and GC soils than in
the XLHT soil (p < 0.05; Fig. 3a) with a lower SOC content and a
lower SOC : N ratio (Table 1). However, the specific EPE-induced CO2
release normalized to SOC content showed no significant difference in the
non-amended soils among the three sites (Fig. 3b), indicating that a similar
proportion of SOC (∼ 4 %) was subject to EPE-induced CO2
release in the alpine and temperate grassland soils (Fig. 3b). The total
EPE-induced CO2 release was significantly higher in the litter-amended
KQ soils than the non-amended ones. Besides the availability of labile OC
provided by litter, the higher total EPE-induced CO2 in litter-amended
KQ soils might be related to its relatively lower soil pH (∼ 7.7) that
facilitates the release rather than the dissolution of respired CO2
(from both SOC and litter mineralization) in soil solution. In addition, KQ
has the highest mean sand content (46.9 %) among the three soils
(Table 1), i.e., the least possible mineral protection on labile OC dissolved
from the litter, and this benefits the transport and mineralization of labile
OC that meanwhile might induce positive priming effects on the SOC
mineralization. We therefore conclude that the KQ soil, with a coarser
texture and a lower pH (Table 1), may have provided less sorptive protection
for the labile DOC components after EPEs (Kell et al., 1994; Nelson et al.,
1994), allowed less dissolution of the respired CO2, and hence showed
a more responsive respiration to the precipitation events. Consequently, we
deduced that the availability of labile organic carbon, soil texture, and pH
are important factors influencing the total EPE-induced CO2 release in
temperate and alpine grassland soils.
Fluxes of dissolved organic carbon (DOC) and dissolved inorganic
carbon (DIC) and volume of leachates from soil columns after extreme
precipitation events (EPEs). Mean values are shown with standard error (n=3). The * and “ns” denote significant and no difference between the
litter-amended and non-amended soils determined by independent sample T
tests, respectively (p < 0.05).
Carbon loss fluxes from soil organic carbon (SOC) mineralization in
the non-amended XLHT soils. Fluxes include EPE-induced CO2 release and leaching of biogenic dissolved inorganic
carbon (DIC), dissolved organic carbon (DOC), and lithogenic DIC. Mean values
are shown with standard error (n=3).
EPE-induced leaching of soil carbon
During the first EPE, a total of 0.57, 0.56, and 0.73 L of leachates were
collected from the XLHT, KQ, and GC soils, respectively. The leachate
increased to 0.71, 0.94, and 0.87 L during the second EPE and was 0.69,
0.83,
and 0.89 L during the third EPE, respectively (Fig. 4). Soil water content
was set to ∼ 60 % of maximum WHC before the first EPE, and leaching
did not occur until soil water reached saturation. Therefore, the leachate
volume was lowest during the first EPE and similar for the second and third
EPEs. There were some variations in the volume of leachates from different
soils, possibly related to preferential flows created during EPEs in the soil
columns (McGrath et al., 2009) and water evaporation between EPEs. DIC was
the main form of carbon in the leachates from the alkaline soils with a high
SIC content (XLHT and GC) but low from the KQ soil with a neutral pH and low
SIC content (Fig. 4). The resulting DIC flux was much higher for the XLHT
soils (∼ 21.3 g C m-2) than the other two (2.9 g C m-2
for KQ and 7.4 g C m-2 for GC soils) during three EPEs, equivalent to
5 times its DOC flux (3.8–4.2 g C m-2; Fig. 4). In contrast, DIC
flux in the KQ soils was only one-third of its DOC flux during EPEs. The form
of leached carbon was mainly linked to the amount of SOC and SIC in the
columns (shown in Fig. S5).
Litter amendment did not increase DOC fluxes in any of the investigated soils
but increased DIC fluxes leached from the KQ soil during the second and third
EPEs and from the GC soil during the second EPE (p < 0.05;
Fig. 4b–c). We postulate that while litter contribution to DOC was minor,
CO2 derived from litter degradation contributed to dissolved CO2 in
soils and hence increased DIC in the leachates (Monger et al., 2015). This
effect was not evident during the first EPE when litter decomposition just
started and was not significant for the third EPE in the GC soil due to a
high sample variability associated with the litter-amended soil (Fig. 4c).
Due to the high SIC content in the XLHT soils (38.15 g per column) and the
low litter OC amendment (0.7 g per column), there was no significant
difference in DIC fluxes between the non-amended and litter-amended XLHT
soils (Fig. 4a). However, for the KQ soil having a relatively low SIC content
similar to the added litter OC (0.7 g per column; Table 1), litter amendment
had a significant effect on the DIC flux (p < 0.05), increasing
by 21 ± 13 and 15 ± 7 % relative to the non-amended KQ soils
during the second and third EPEs, respectively. There was also a
30 ± 19 % increase in the DIC flux from the litter-amended GC soils
relative to its non-amended counterpart during the second EPE. Therefore,
litter amendment had a significant influence on DIC fluxes from soils with a
relatively low SIC content (KQ and GC) under EPEs compared with the high-SIC
XLHT soil.
Between different EPEs, leachate DOC fluxes did not vary in any of the
investigated soils. By comparison, DIC fluxes increased in the XLHT soil from
4.5 g C m-2 after the first EPE to 9.0 g C m-2 after the third
EPE (p < 0.01; Fig. 4). This increase may be caused by (i) an
increased contribution of SOC degradation to soil DIC and/or (ii) an elevated
dissolution of soil carbonates induced by higher soil CO2 concentrations
with repeated EPEs (Gulley et al., 2014; Ren et al., 2015). To evaluate these
contributions, the δ13C values of DIC were measured for the
non-amended XLHT soil. The δ13C of leached DIC ranged from -10.0
to -6.6 ‰ during the first EPE. Based on the isotopic mass balance
of Eqs. (3) and (4), lithogenic carbonate (with a δ13C value of
0 ‰) contributed 51 % to the leached DIC, while biogenic DIC
produced by SOC degradation contributed 48 % (Fig. 5). The δ13C
value of leached DIC decreased to -12.3 and -13.5 ‰ during the
second and third EPEs, corresponding to a contribution of 77 and 84 % by
biogenic sources in the total DIC, respectively (Fig. 5). These results
confirm our previous hypothesis that SOC decomposition contributed
significantly to soil DIC fluxes. Combined with the total flux rate, we
calculated that both lithogenic and biogenic DIC fluxes were
∼ 2.1 g C m-2 in the first EPE. Subsequently, lithogenic DIC
flux decreased to ∼ 1.3 g C m-2, while biogenic DIC flux
increased to 7.6 g C m-2 in the third EPE. This demonstrates that the
increased DIC flux with repeated EPEs was mainly derived from an increased
contribution of SOC mineralization. Interestingly, increasing DIC fluxes with
repeated EPEs were not observed in the KQ and GC soils (Fig. 4) despite their
higher SOC contents (Table 1) and CO2 release rates (Fig. S3). Given
that the XLHT soil had the highest soil pH, the high alkalinity may have
favored the retention of respired CO2 in the soil solution compared with
the other soils (Parsons et al., 2004; Yates et al., 2013; Liu et al., 2015),
leading to its high contribution to DIC fluxes.
Regardless of its source, the EPE-induced leaching loss of inorganic carbon
was 31.5 and 10.6 µg DIC g-1 soil from the alkaline XLHT and
GC soils, respectively, which is approximately 3 and 5 times higher than the
corresponding DOC leaching loss (5.9 and 3.9 µg DOC g-1 soil,
respectively). However, the KQ soil had a relatively lower EPE-induced DIC
loss (4.4 µg DIC g-1 soil) than the DOC leaching loss
(11.6 µg DOC g-1 soil) mainly due to its lower initial SIC
content and relatively neutral soil pH value. Hence, total DIC (biogenic
DIC + lithogenic DIC) was the main form of soil carbon loss in alkaline
soils during EPEs. When the source of the leached DIC is taken into account,
the dissolution of CO2 produced by SOC mineralization (biogenic DIC)
constituted more than half of the leached DIC (at least from the XLHT soils;
Fig. 5), whose contribution increased with recurring EPEs (Fig. 5). This
implies that SOC mineralization during the three EPEs was underestimated by
approximately a factor of 8 when measured as CO2 gas flux from the soil into
the column headspace only (Fig. 5). In addition, DIC loss exclusively
resulting from SIC dissolution or weathering was also a significant fraction
of soil carbon loss, equivalent to 219 % SOC loss in the form of
EPE-induced CO2 during EPEs (Fig. 5). These results collectively
corroborate the evidence that inorganic carbon loss is the main form of soil carbon loss
in alkaline soils during EPEs.
Relationship of dissolved inorganic carbon (DIC) and dissolved
organic carbon (DOC) fluxes with soil properties: (a) DIC flux with
total inorganic carbon in the soil columns; (b) DIC flux with soil
pH; (c) DOC flux with silt and clay content of soils; (d)
total soil carbon flux with soil pH; (e) DOC flux with leachate
volume; (f) DIC flux with leachate volume. Mean pH values are shown
with standard error (n=3).
As for the influencing factors on soil carbon leaching loss, the DIC flux was
positively correlated with the amount of SIC in the soil columns and soil pH
(p < 0.05; Fig. 6a–b). These two relationships may be
self-correlated due to a positive relationship between soil pH and SIC (Liu
et al., 2016). By comparison, DOC flux was linked with the amount of SOC in
the soil columns, but decreased with an increasing content of silt and clay
(p < 0.05; Fig. 6c). This may be explained by the stronger
retention of SOC on small-sized particles with more sorption sites (Barré
et al., 2014; Mayer, 1994). Interestingly, neither DOC nor DIC fluxes showed
any significant relationships with the volume of leachates during EPEs
(Fig. 6e–f). This indicates that we used a sufficient amount of precipitation
in this study to “scavenge” dissolved carbon from soils, and hence these
fluxes represent the soil carbon leaching potential under EPEs. Overall, total
soil carbon loss through leaching under EPEs was positively related to soil
pH values (p < 0.05; Fig. 6d), suggesting that soil pH is a
critical factor determining the magnitude of soil carbon loss under EPEs.
Leaching fluxes of dissolved organic carbon (DOC) and dissolved
inorganic carbon (DIC) in this study compared with those reported in the
literature. 1 n = 110; data from Brooks et al. (1999), Fröberg et
al. (2005, 2006, 2011), Gielen et al. (2011), Kindler et al. (2011), Lu et
al. (2013), Michalzik et al. (2001), Sanderman et al. (2009).
2 n = 33; data from Brye et al. (2001), Kindler et al. (2011),
Siemens et al. (2012), Walmsley et al. (2011), Wang and Alva (1999), Gerke et
al. (2016), Herbrich et al. (2017), Rieckh et al. (2014), Lenz (2014).
3 n = 46; data from Brooks et al. (1999), Brye et al. (2001),
Ghani et al. (2010), Kindler et al. (2011), McTiernan et al. (2001), Parfitt
et al. (2009), Sanderman et al. (2009), Tipping et al. (1999).
4 n = 8; data from Kindler et al. (2011). 5 n = 32;
data from Kindler et al. (2011), Siemens et al. (2012), Walmsley et
al. (2011), Wang and Alva (1999), Gerke et al. (2016), Herbrich et
al. (2017), Rieckh et al. (2014), Lenz (2014). 6 n = 9; data from
Brye et al. (2001), Kindler et al. (2011). Lowercase letters (a1,
b1 and a2, b2) represent significant difference levels of DOC
and DIC fluxes, respectively, in different ecosystems determined by Duncan's multiple range
test (one-way ANOVA, p < 0.05). Dashed lines
represent mean values for the investigated soils.
Main pathways of grassland soil carbon loss under EPEs
In this study, EPE-induced soil carbon loss was composed of three parts:
leachate DIC including lithogenic and biogenic DIC, leached DOC, and
EPE-induced CO2 emission into the column headspace. Total DIC and DOC
fluxes accounted for 90, 62, and 68 % of EPE-induced total loss at XLHT,
KQ, and GC, respectively, representing the major pathway of soil carbon loss
in these grassland soils under EPEs. Soil carbon leaching fluxes were 25.3,
10.4, and 10.1 g C m-2 yr-1 in XLHT, KQ, and GC soils during
three EPEs, respectively, with DIC as the dominant form in XLHT and GC soils.
While DIC fluxes found for the KQ and GC soils generally fell within the
range reported for grassland soils (1.3–47.8 g C m-2 yr-1;
Parfitt et al., 1997; Brye et al., 2001; Kindler et al., 2011), the XLHT soil
had a DIC flux higher than the majority (> 50 %) of the
reported values (Fig. 7). This may be attributed to the higher SIC content
and stronger dissolution of respired CO2 in the XLHT soils due to its
higher soil pH (9.1 ± 0.1) relative to other grassland soils (pH:
5.4–7.5; Kindler et al., 2011) and the high intensity of our simulated EPEs
(precipitation: 40 mm h-1). Nonetheless, the DIC fluxes in grassland soils
reported in this study and elsewhere (Brye et al., 2001; Kindler et al.,
2011) were significantly higher than in forest and cropland ecosystems
(p < 0.05; Rieckh et al., 2014; Lentz and Lehrsch, 2014; Gerke et
al., 2016; Herbrich et al., 2017; Siemens et al., 2012; Walmsley et al.,
2011; Wang and Alva, 1999; Kindler et al., 2011), highlighting the importance
of leaching as a major pathway of soil carbon loss in grasslands. By
contrast, DOC fluxes in this study (4.8 ± 2.5 g C m-2) were
lower than most of the reported values in forest and grassland ecosystems due
to the low SOC contents in our soils (Fig. 7).
Net ecosystem production (NEP) in the temperate steppe of Inner Mongolia
(XLHT and KQ) is 8.7 g C m-2 yr-1 (Sui and Zhou, 2013). While
the EPE-induced CO2 release (2.8 ± 0.6 and
6.3 ± 3.0 g C m-2) accounted for 32 and 72 % of the NEP at
XLHT and KQ, respectively, soil carbon leached during three EPEs was
equivalent to 290 and 120 % of NEP, with total DIC loss accounting for
244 and 33 %, respectively. It is worth mentioning that biogenic DIC loss
(16.0 ±3.4 g C m-2) caused by SOC degradation accounted for
184 % of NEP at XLHT, indicating the importance of biogenic DIC to
leached inorganic carbon loss during EPEs. By comparison, NEP in the studied
alpine grassland (68.5 g C m-2 yr-1; Fu et al., 2009) is much
higher than in typical temperate steppe. Hence, soil carbon loss through
leaching and respired CO2 release accounted for 15 % (DIC: 11 %,
DOC: 4 %) and 7 % of the NEP at GC, respectively. Nonetheless, the
EPE-induced soil carbon loss relative to NEP was higher in this study than
that estimated for grassland topsoil across Europe (12 % for DIC loss,
2 % for DOC loss; Kindler et al., 2011) where the net ecosystem exchange
(NEE) reported by Kindler et al. was used as NEP according to the report of
Kirschbaum et al. (2001). This was partially attributed to the lower NEP and
higher SIC content in XLHT and KQ soils, underscoring the fact that soil carbon
leaching is more important in fragile ecosystems with low productivity.
The uncertainty related to the importance of leaching processes in the overall
carbon budget along the “soil–river–ocean” continuum is in the ultimate
downstream fate of the leached carbon. If part of this carbon is retained in
the surrounding soils or carried along from the river to the ocean in the
form of DIC without outgassing into the air, it will not constitute a source
of atmospheric CO2 on a relatively short term (over years or decades).
However, soil columns used in our study have a depth (60 cm) typical of or
even deeper than the average soil depth in the alpine grasslands of
the Qinghai–Tibetan Plateau (Wang et al., 2001). Hence, we assume that the carbon
leached in our experiments will have minimum retention in the soil.
Furthermore, compared to DOC and DIC in the soil solution, the leached carbon
is more likely to be subject to more intensified mineralization and
outgassing during the land–ocean transfer given more intensified mixing
processes, oxygen exposure, and photooxidation of terrestrial carbon upon
releasing into the river (Hedges et al., 1997; Battin et al., 2009). Hence,
we postulate that carbon leached from soils is more vulnerable to
decomposition and/or release compared to that retained in the soil. That
being said, it will be necessary to confirm our results and hypothesis using
field-based leaching experiments to better understand the ultimate fate of
leached soil carbon and whether it will be retained in the deeper soil or show
higher degradability upon leaving the soil matrix. Such information will be
complementary to our study and further elucidate the importance of leaching
processes in terms of ecosystem carbon budget.
In summary, this study quantified and compared soil carbon loss through
respired CO2 release and leaching in three typical grassland soils of
northern China under simulated EPEs. Soil CO2 release was stimulated
shortly after each EPE, leading to an EPE-induced CO2 release equivalent
to 32 and 72 % of the NEP at XLHT and KQ (temperate grasslands) and
7 % at GC (alpine grassland). By comparison, total soil carbon leaching
fluxes accounted for 290, 120 and 15 % of the NEP at XLHT, KQ, and GC,
respectively, with DIC as the main form of carbon loss in the SIC-enriched
XLHT and GC soils. In view of DIC sources, biogenic DIC loss derived from SOC
mineralization contributed to more than half of the total leached DIC fluxes
and accounted for 184 % of the NEP at XLHT. Moreover, DIC loss increased
with recurring EPEs in the XLHT soil with the highest pH due to the increased
dissolution of soil carbonates and an elevated contribution of dissolved
CO2 from SOC degradation. These results also imply that SOC
mineralization in alkaline grassland soils during EPEs might be
underestimated if measured only as CO2 emission from soil into the
atmosphere. Admittedly, our results are based on artificial soil columns
that destroyed natural soil structures, hence potentially increasing the
contact between pore water and soil particles through changing soil porosity.
Also, soil water content was set to ∼ 60 % of maximum WHC initially
in our experiment, which is higher than that in the field of temperate grasslands
(XLHT and KQ). Thus, our measured DOC and DIC fluxes are likely to be higher
than carbon leaching in the field due to greater water retention in drier
soils. Hence, our estimate may represent an upper limit of soil carbon
leaching potential under EPEs. Nonetheless, these results highlight the fact that
leaching loss of soil carbon, especially in the form of DIC originated from
biogenic and lithogenic carbonates, plays an important role in the regional
carbon budget of grasslands located in arid and semiarid regions. Further
research effort is needed to combine short-term laboratory experiments with
long-term field measurements to fully assess the impacts of EPEs on the soil
carbon budget in these areas. In addition, with a projected increase in EPEs
under climate change, soil carbon leaching processes and the influencing
factors warrant a better understanding and should be incorporated into soil
carbon models when estimating carbon balance in grassland ecosystems.