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\begin{document}

\title{Phytolith-occluded carbon sequestration potential in three major steppe
types along a precipitation gradient in Northern China}



\author[1]{Qi Limin}%
\author[1]{Sun Tingyu}%
\author[1]{Guo Xudong}%
\author[1]{Guo Ying}%
\author[1]{Frank Li}%
\affil[1]{Inner Mongolia University}%


\vspace{-1em}



  
  \date{May 23, 2024}


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\selectlanguage{english}
\begin{abstract}
Phytolith-occluded carbon (PhytOC) is an important long-term stable
carbon fraction in grassland ecosystems, and plays a promising role in
global carbon sequestration. Determination of the PhytOC traits of
different plants in major grassland types is crucial for precisely
assessing their PhytOC sequestration potential. Precipitation is the
predominant factor in controlling net primary productivity (NPP) and
species composition of the semiarid steppe grasslands. We selected three
representative steppe communities of desert steppe, dry typical steppe
and wet typical steppe in Northern Grasslands of China along a
precipitation gradient, to investigate their species composition,
biomass production and PhytOC content for quantifying its long-term
carbon sequestration potential. Our results showed that (i) the
phytolith and PhytOC contents in plants differed significantly among
species, with dominant grass and sedge species having relatively high
contents, and the contents are significantly higher in below- than the
aboveground parts. (ii) The phytolith contents of plant communities were
16.68, 17.94 and 15.85 g kg-1 in the above- and 85.44, 58.73 and 76.94 g
kg-1 in the belowground biomass of desert steppe, dry typical steppe and
wet typical steppe, respectively; and the PhytOC contents were 0.68,
0.48 and 0.59 g kg-1 in the above- and 1.11, 0.72 and 1.02 g kg-1 in the
belowground biomass of the three steppe types. (iii) Climatic factors
affected phytolith and PhytOC production of steppe communities mainly
through altering plant production, whereas their effects on phytolith
and PhytOC contents were relatively small. Plant aboveground biomass and
PhytOC content were strongly associated with the current-year climate
and soil bio-available Si content; while plant belowground biomass and
PhytOC content were relatively stable, and their variation across the
sites is in accordance with the spatial variation in the long-term means
of climatic and soil factors, reflecting the perenniality of plant
belowground part.%
\end{abstract}%



\sloppy


\textbf{1 INTRODUCTION}

Climate warming and the increase of extreme climatic events are mostly
attributed to the increasing concentrations of greenhouse gases in the
atmosphere, especially carbon dioxide (CO\textsubscript{2}). The coupled
biogeochemical cycles of carbon (C) and silicon (Si) in the terrestrial
system are deemed a mechanism that impacts the long-term regulation of
atmospheric CO\textsubscript{2} (Berner, 1992; Parr et al., 2010; Parr
\& Sullivan, 2011; Song et al., 2012a; Song et al., 2012b). Plants
absorb mono-silicic acid from soil solution via their roots (Epstein,
1994; Ma \& Yamaji, 2006) and deposit silica (SiO\textsubscript{2}) in
plant tissues as phytoliths (Hodson et al., 2005; Schaller et al.,
2013). Approximately 0.1\%-6.0\% organic C in plants is reported to be
incorporated in phytoliths during their formation, and is referred to as
phytolith-occluded carbon (PhyOC) (Bartoli \& Wilding, 1989; Jones \&
Milne, 1965; Zuo \& L\selectlanguage{ngerman}ü, 2011). Phytoliths exist in most plants, and
their content in plant tissues varies among plant species, ranging from
less than 0.5\% in most dicotyledons, 1\%-3\% in dryland grasses, and up
to 10\%-15\% in the Cyperaceae and wetland Poaceae species (Epstein,
1994). Phytoliths are mainly deposited in the cell wall, cell lumen and
intercellular spaces or the extracellular layer in plant issues
(Epstein, 2009; Hodson et al., 2005; Ma \& Yamaji, 2006; Schaller et
al., 2013); after plants' death, the phytoliths can be incorporated into
soil or sediments after the decomposition of plant litter (Blecker et
al., 2006). Since phytoliths are resistant to decomposition, PhytOC can
be preserved in soil or sediments with the Si-coat protection for
several hundred or thousand years, and may account for 82\% of the total
organic carbon in some old soils (Parr \& Sullivan, 2005; Song et al.,
2017). The formation and stability of PhytOC in the coupled
biogeochemical cycling of C and Si has been increasingly recognized as a
promising mechanism of terrestrial ecosystems to sequester atmospheric
CO\textsubscript{2}, which has motivated many researchers to quantify
the PhytOC sequestration potential of various systems (Parr et al.,
2010; Parr \& Sullivan, 2011; Song et al., 2012a).

Grasslands are an important terrestrial ecosystem covering more than
one-fifth of the world's land surface (Scurlock \& Hall, 2010). The
large distribution area and the high PhytOC concentration in grassland
plants, especially Poaceae and Cyperaceae species (Epstein, 1994;
Clarkson \& Hanson, 1980), make grassland a particularly important
long-term C sequestration process (Blecker et al., 2006; Song et al.,
2017). Several studies assessed the PhytOC sequestration potential of
grasslands (Pan et al., 2017; Qi et al., 2016; Song et al., 2012a). Song
et al. (2012a) reported that phytolith and PhytOC production rates in
aboveground biomass of grassland were significantly influenced by their
aboveground net primary productivity (ANPP); Qi et al. (2016) suggested
that the belowground productivity of plants could play a dominant role
in PhytOC production in grassland ecosystems; and Ji et al. (2018)
reported that Si distribution in the aboveground parts, thus the PhytOC
sequestration potential, of grassland plants, varies markedly among
plant species and across grassland types. However, the effects of
grassland type and species composition on the production rate of
phytoliths and PhytOC (including the above- and belowground parts) are
still not fully understood. Precipitation is the predominant climatic
factor that controls plant species composition and net primary
productivity (NPP) of grassland ecosystems in semi-arid steppe region
(Bai et al., 2004; Dai et al., 2012; Hou et al., 2014), thus affecting
the PhytOC sequestration potential. As such, it is necessary to
investigate the PhytOC production rate in different grassland types
along climatic gradient, for accurate estimation of PhytOC sequestration
potential and prediction of their response to climate changes. In
present study, we selected three representative vegetation types in
climatically different regions alone a precipitation gradient in Inner
Mongolia, that is, the desert steppe, the dry typical steppe, and the
wet typical steppe regions, to study their PhytOC production.
Specifically, we aimed to investigate the species composition, and
measure the phytolith and PhytOC contents of the major plant species, of
these grassland types, so as to increase the accuracy in estimating
phytoliths and PhytOC production and storage in plant communities, and
analyze their relations with climatic factors. We hypothesized that
along the gradient of climate aridity increase (that is, precipitation
decrease) from the wet dry steppe site, via the dry typical steppe site
to the desert steppe site, the grassland NPP would decrease, while the
contents of phytoliths and PhytOC in the steppe plants would increase
due to the intense plant transpiration but low biomass production.

\textbf{2 MATERIALS AND METHODS}

\textbf{2.1 Sampling sites}

This study was conducted at three sites in the steppe region of central
Inner Mongolia along a climatic gradient of increasing annual
precipitation, that is, at a desert steppe site (within Sunite Right
Banner, at 43°511'N, 113°42'E), a dry typical steppe site (within
Maodeng farm of Xilinhot city, at 44°50'N, 116°36'E), and a wet typical
steppe site (within West Ujimqin Banner, at 45°43'N, 118°30'E). The
region experiences a temperate semiarid climate. The mean annual
temperature (MAT) are -0.9, 2.9 and 4.9\selectlanguage{english}, and mean annual precipitation
(MAP) are 182, 278 and 342 mm, respectively at the desert steppe, dry
typical steppe and wet typical steppe sites; and 75\%-85\% of annual
precipitation falls in the plant growing seasons from May to September
(average of the 1960-2016 period). In the year for field study (2016),
the annual precipitation was 189, 309 and 299 mm, and the plant
growing-season precipitation was 129, 215 and 237 mm, respectively in
the desert steppe, dry typical steppe and wet typical steppe sites. The
desert steppe site is on a calcic brown soil, whereas the other two
steppe sites are on chestnut soil. The humus layer is 15-30 cm in depth,
and the calcic horizon (mostly CaCO\textsubscript{3}) is 30-60 cm in
depth, both increasing from desert steppe to dry typical steppe and wet
typical steppe. The dominant species of the vegetation are \emph{Stipa
klemenzii, Cleistogenes songorica, Allium bidentatum} and \emph{Salsola
collina} in the desert steppe, \emph{Leymus chinensis, Stipa
krylovii}and \emph{Cleistogenes squarrosa} in the dry typical steppe,
and\emph{Leymus chinensis, Stipa grandis} and \emph{Cleistogenes
squarrosa}in the wet typical steppe (Table 2).

\textbf{2.2 Field sampling}

All the three sampling sites were located on flat ground with
representative native steppe communities. The sites were fenced to
exclude animal grazing at the beginning of the plant growing season in
2016, and plant and soil samples were collected from these sites at the
end of August. At each site, five quadrates of 1m x1m were set up at the
center and four corners of a delineated area of 20 mx20 m, and all
standing live and dead vascular plants (that was obviously produced
during the current season) in these quadrats were harvested at ground
level species by species, dried to a constant weight at 65\selectlanguage{english} and weighed.
The dry mass of all plant species per quadrat averaged over five
replicates was used to determine the aboveground plant biomass at peak
plant biomass time, and this was also used to approximate ANPP of the
grassland (Scurlock et al., 2002). The belowground biomass and its
distribution profile (0-70 cm) were measured using the soil coring
method, and BNPP (during the plant growing season from May to October)
of the studied grassland was obtained from previous studies (Chai et
al., 2014; Hou et al., 2014).

Whole plants of dominant species at each site were collected by digging
up each individual to a depth of 20 cm below ground level, and then each
individual was cut into two parts: aboveground part (shoots) and
belowground part (noted as roots, but it includes plant roots and
rhizomes as well as shoot stumps buried below the soil surface). A
sample of about 300g dry matter of the shoots and the roots of each
plant species was collected in each of the three plots at each site. The
samples were washed with deionized water, dried at 65\selectlanguage{english} and then cut into
pieces (\textless{}5mm) for phytolith analysis.

The soil bulk density and moisture content were obtained by the
cutting-ring method and the oven drying method (at 105\selectlanguage{english}). The soil
samples were collected using soil cores (diameter =7cm) and air dried at
ambient temperature in laboratory.

\textbf{2.3 Sample analysis}

The phytoliths within plant parts were extracted using a microwave
digestion process (Parr et al., 2001) followed by a Walk-Black type
digestion to ensure the purity of the phytoliths (Parr \& Sullivan,
2014; Walkley \& Black, 1934). Two duplicates were analyzed for each
plant sample. The exacted phytoliths were dried at 65\selectlanguage{english} to a constant
weight. The PhytOC was determined using the PhytOC alkalidis solution
spectrophotometer method (Yang et al., 2014). In this method, sodium
hydroxide solution was used to dissolve the Si compound in order to
release the occluded organic carbon from the phytoliths, then potassium
dichromate
(K\textsubscript{2}Cr\textsubscript{2}O\textsubscript{7})-sulfuric acid
(H\textsubscript{2}SO\textsubscript{4}) solution was used to oxidize the
released organic carbon, and the concentration of
Gr\textsuperscript{3+}produced in this oxidation was determined by
spectrophotometer with its absorbance at 590 mm wavelength. The organic
carbon concentration was calculated based on the amounts of potassium
dichromate consumed, and the accuracy and repeatability of the method
was well verified against the results obtained with acid
dissolution-Elementar Vario MAX CN method (Germany) (Yang et al., 2014).
The phytoliths and PhytOC contents of the two parts of each plant
species were calculated as the average of the three replicate plots. For
each species, the ratio of aboveground to belowground biomass
(shoots/roots) was calculated based on the sampled plant individuals.
The ratio was used to calculate the belowground biomass of the species
in 1 m\textsuperscript{2} based on the measured aboveground biomass of
the species. The estimation of plant root biomass in the soil profile
and the turn-over rate of the belowground biomass were quoted from
previous studies (Chai et al., 2014; Hou et al., 2014).

The air dried soil samples were separated into the 100 mesh soil samples
and the 10 mesh soil samples. The soil organic carbon (SOC) was
determined with the 100 mesh soil samples using the method of classical
potassium dichromate (Walkley \& Black, 1934), and the soil pH and
bioavailable Si content were analyzed with 10 mesh soil samples using a
pH meter (Yang et al., 2018) and silicomolybdic acid method (Yang et
al., 2018), respectively.

\textbf{2.4 Data calculations and statistics}

The formula for calculating phytolith and PhytOC contents in plant
species were as follows:

phytolith content (g kg\textsuperscript{-1}) = phytolith weight (g) /
dry biomass (kg) {[}1{]}

PhytOC content (g kg\textsuperscript{-1}) = PhytOC weight (g) / dry
biomass (kg) {[}2{]}

The community weighted mean contents of phytolith
(Phytolith\textsubscript{CWM}) and phytOC (PhytOC\textsubscript{CWM})
were also calculated using biomass as weight:

phytolith\textsubscript{CWM} (g
kg\textsuperscript{-1})=\selectlanguage{english}[?]\emph{\textsubscript{i}} phytolith
content\emph{\textsubscript{i}} (g
kg\textsuperscript{-1})xbiomass\emph{\textsubscript{i}} (\%) {[}3{]}

PhytOC\textsubscript{CWM} (g
kg\textsuperscript{-1})=\selectlanguage{english}[?]\emph{\textsubscript{i}} PhytOC
content\emph{\textsubscript{i}}(gkg\textsuperscript{-1})xbiomass\emph{\textsubscript{i}}
(\%) {[}4{]}

where \emph{i} enumerates each species.

PhytOC stock (kg ha\textsuperscript{-1})= PhytOC\textsubscript{CWM} (g
kg\textsuperscript{-1})xbiomass (kg
ha\textsuperscript{-1})x10\textsuperscript{-3} {[}5{]}

PhytOC production flux (kg ha\textsuperscript{-1}yr\textsuperscript{-1})
= PhytOC\textsubscript{CWM}(gkg\textsuperscript{-1})xNPP (kg
ha\textsuperscript{-1}yr\textsuperscript{-1})x10\textsuperscript{-3}
{[}6{]}

One-way ANOVA and Duncan's multiple range test were performed to examine
the difference in phytolith and PhytOC contents among different parts of
plant species. SPSS 20.0 was used for all the statistics and Sigma Plot
12.0 was used for figures.

\textbf{3 RESULTS}

\textbf{3.1 Soil properties at the three steppe sites}

Soil physical and chemical properties differed among the three sites
(Table 1). Soil bulk density was higher in wet typical steppe than other
steppes (\emph{P} \textless{}0.05). Soil moisture and the SOC content
increased, while soil pH decreased, from desert steppe to dry typical
steppe, and wet typical steppe (\emph{P} \textless{}0.05). The
bioavailable Si content in soil showed no significant difference among
the three sites.

\textbf{3.2 Plant above- and belowground biomass}

Eight, seven and three dominant species were sampled respectively in the
desert steppe, dry typical steppe and wet typical steppe communities to
determine their phytolith and PhytOC contents; these species contributed
to 87.58\%, 93.65\% and 94.39\% of the aboveground biomass of the three
plant communities (Table 2). The measured aboveground community biomass
were 562.27+-49.28, 1471.99+-110.82 and 1120.09+-52.98 kg
ha\textsuperscript{-1}, and the estimated belowground biomass (0-70cm)
were 4227.99+-456.20, 8639.89+-543.77 and 8643.74+-491.55 kg
ha\textsuperscript{-1} in the desert steppe, dry typical steppe and wet
typical steppe, respectively. The biomass of major plant species in
these communities were shown in Table 3.

\textbf{3.3 Phytolith and PhytOC contents in grassland plants}

Phytolith and PhytOC contents in the above- and belowground biomass
varied substantially among plant species, and across grassland types
(Fig.1, Fig.2). In the aboveground part, the phytolith content was
highest in \emph{Carex duriuscula} (39.96+-2.21 g kg\textsuperscript{-1})
and lowest in \emph{Salsola collina} (4.23+-0.09 g
kg\textsuperscript{-1}) in desert steppe. The phytolith content in
belowground biomass varied from 7.99+-1.34 g kg\textsuperscript{-1}
in\emph{Salsola collina} in desert steppe to 126.0+-9.86 g
kg\textsuperscript{-1} in \emph{Stipa grandis} in wet typical steppe.
The PhytOC content in aboveground biomass was in the range of 0.23+-0.06
g kg\textsuperscript{-1} in \emph{Salsola collina} to 3.63+-0.73 g
kg\textsuperscript{-1} in \emph{Allium bidentatum} in desert steppe; the
PhytOC content in belowground biomass was also lowest in \emph{Salsola
collina} (0.40+-0.13 g kg\textsuperscript{-1}), but highest
in\emph{Scorzonera divaricata} (1.96+-0.09 g kg\textsuperscript{-1}) in
desert steppe (Fig.2).

\textbf{3.4 Community-weighted mean contents of phytolith and PhytOC}

The community-weight mean phytolith content
(phytolith\textsubscript{CWM}) and PhytOC content
(PhytOC\textsubscript{CWM}) in the above- and belowground plant biomass
were calculated. As plant belowground biomass was measured at species,
not community level, the relative belowground biomass of each species
was estimated using the measured relative aboveground biomass (AGB\%)
and the shoot/root ratio (A/B) of each species, and used to calculate
the community weighted mean phytolith content of belowground biomass.

The phytolith\textsubscript{CWM} was 16.68, 17.94 and 15.85 g
kg\textsuperscript{-1} respectively in the aboveground biomass of desert
steppe, dry typical steppe and wet typical steppe, no significant
difference being detected among the three steppe types (\emph{P}
\textgreater{}0.05); the PhytOC\textsubscript{CWM} in the belowground
biomass was neither significantly different among the three steppe types
(\emph{P} \textgreater{}0.05), being 86.44, 58.73 and 76.94 g
kg\textsuperscript{-1} for the desert steppe, dry typical steppe and wet
typical steppe, respectively (Fig.3). The PhytOC\textsubscript{CWM}was
0.68 g kg\textsuperscript{-1} in the aboveground biomass of desert
steppe, which was higher than in that of dry typical steppe (0.48 g
kg\textsuperscript{-1}) or wet typical steppe (0.59 g
kg\textsuperscript{-1}). The PhytOC\textsubscript{CWM} in the
belowground biomass was 1.11, 0.72 and 1.02 g
kg\textsuperscript{-1}respectively in desert steppe, dry typical steppe
and wet typical steppe, with no significant difference among these
steppes (\emph{P} \textgreater{}0.05) (Fig.3).

\textbf{3.5 The PhytOC sequestration potential and its relations with
environmental factors}

The PhytOC stock in the aboveground biomass ranged from 0.38+-0.07 to
0.71+-0.09 kg ha\textsuperscript{-1}, and was significantly lower in
desert steppe than in two typical steppes (\emph{P} \textless{}0.05);
and PhytOC stock in the belowground biomass ranged from 4.67+-0.16 to
8.79+-0.36 kg ha\textsuperscript{-1}, and was significantly lower in
desert steppe and dry typical steppe than in wet typical steppe
(\emph{P} \textless{} 0.05) (Table 3).

The PhytOC production flux of steppe communities were estimated based on
the NPP and its PhytOC content, and were 0.38, 0.71 and 0.66 kg
ha\textsuperscript{-1} yr\textsuperscript{-1} from the aboveground part
(ANPP), and 7.88, 9.14 and 21.01 kg
ha\textsuperscript{-1}yr\textsuperscript{-1} from the belowground part
(BNPP), respectively in the desert steppe, dry typical steppe and wet
typical steppe (Table 3).

Both plant community aboveground biomass (AGB) and PhytOC content varied
significantly across sites; these two plant parameters, and soil
bioavailable Si content change synchronously with the current-year
annual precipitation (Spearman rank correlation coefficient is 1 among
these factors). In contrast, the variation in plant community
belowground biomass (BGB) and PhytOC content across sites was more
correlated with the long-term mean values of environmental factors, such
as mean annual precipitation (MAP) and temperature (MAT), soil bulk
density, pH and SOC content (Spearman rank correlation coefficient is 1
among these factors).

\textbf{4 DISSCUSSION}

\textbf{4.1 Phytolith and PhytOC contents in grassland ecosystems}

The dominant plant species of grasslands, belonging to Poaceae and
Cyperaceae, are Si accumulators (Conley, 2002; Epstein, 1994; Stromberg
et al., 2016), and deposit Si mostly in phytoliths (Hodson et al., 2005;
Schaller et al., 2013). In the present study, the highest phytolith
content in the aboveground parts of plants was detected in \emph{Carex
duriuscula} , a perennial Cyperaceae, whereas the lowest content was
in\emph{Salsola collina} , an annual Chenopodiaceae, consistent with
results from other studies (Ru et al., 2018). The highest phytolith
content in the belowground parts was detected in \emph{Stipa grandis} ,
a perennial bunchgrass, whilst the lowest was also in \emph{Salsola
collina} . Even though a high Si content is not a general feature of
monocots (Hodson et al., 2005), many monocots accumulate more Si than
non-monocots (Epstein, 1994). In the present study, phytolith contents
averaged 22.40 and 57.25 g kg\textsuperscript{-1} respectively in the
above- and belowground parts of monocots, higher than that in the above-
and belowground parts of dicots, respectively 9.14 and 35.88 g
kg\textsuperscript{-1}.

Both species composition and NPP of plant communities vary substantially
along climatic gradient in semi-arid regions (Bai et al., 2004; Dai et
al., 2012; Hou et al., 2014), whilst the biomass-weighted mean phytolith
or PhytOC contents does not show a significant difference among steppe
types (Fig. 3). This is because that the dominant species in the studied
steppe communities at the three sites are phylogenetically close (i.e.,
belong to the same genera), thus have similar phytolith or PhytOC
contents, and contribute to a large proportion of community biomass. For
example, \emph{Stipa} species are dominants in all the three steppe
sites, with their AGB (either of \emph{S. klemenzii, S. grandis}
or\emph{S. krylovii} ) contributing to 45.79\%, 53.25\% and 48.42\% of
the community AGB respectively in the desert steppe, dry typical steppe
and wet typical steppe. Also, dominant \emph{Cleistogenes songorica}
or\emph{C. squarrosa} accounts for 15.59\%, 9.35\% and 25.04\% of the
community AGB respectively in these three sites. As a result, the
variation in community phytolith or PhytOC contents has much smaller
effects on its production flux (= phytolith or PhytOC content x NPP)
across the steppe sites, and the variation in phytolith or PhytOC
production flux is mainly associated with the changes in NPP. This
indicates a predominant role played by plant above- and belowground
biomass production along the climate gradient for the phytolith and
PhytOC production, which overshadows the effects of the variation in
plant PhytOC content at community level.

The significantly higher PhytOC content in the below- than the
aboveground biomass, is most likely associated with the perenniality of
plants, the PhytOC in the aboveground part is deposited in the current
year, whereas that in the belowground part may be deposited in multiple
years (Qi et al. 2016). The higher PhytOC content in the aboveground
part of desert steppe community than that of typical steppe communities
is consistent with our hypothesis that the intense transpiration
required for Si deposition in plant tissues in the desert steppe
contributed to the higher PhytOC content. However, the PhytOC production
flux is significantly lower in desert steppe community than the typical
steppes due to its lower NPP.

The PhytOC content in plants is associated with the silica deposition,
thus with the amount of plant Si uptake (Parr et al., 2009; Li et al.,
2013a). The environment factors, such as climate and soil conditions,
may influence plant Si uptake, thus the efficiency of PhytOC
accumulation in plants (Pan et al., 2017; Li et al., 2013a; Yang et al.,
2018). In our study, low pH and high SOC can account for the higher
phytolith accumulation in wet than dry typical steppe, which is
consistent with the results in previous report (Song et al., 2012b). A
higher pH and moisture content accelerate Si to dissolve in soil
solutions (Fraysse et al., 2009; Yang et al., 2018), and to be taken up
by plants and transpired in vascular bundles in plants (Epstein, 2009;
Parr et al., 2009). Pan et al. (2017) reports that soil
SiO\textsubscript{2} content shows no significant difference among the
grassland sites with different degradation levels, while bioavaliable Si
content in the top soil of non-degraded grassland was relatively lower
due to more bioavailable Si being absorbed by plants at the site. In
studied steppes, the bioavailable Si content in the soil was higher in
dry steppe site than in other two sites, which is probably resulted from
the less uptake of bioavailable Si from the soil at this site, as its
phytolith accumulation was lower than in other two steppe sites.

\textbf{4.2 PhytOC long-term sequestration potential}

Many previous studies have assessed the potential of PhytOC
sequestration in various ecosystems, such as forest, grassland, wetland
and agriculture ecosystems (Parr et al., 2010; Parr et al., 2009; Li et
al., 2013b; Zuo et al., 2011). But most of these assessment are based on
the PhytOC production in plant aboveground biomass, ignoring that in
belowground biomass. A recent study (Chen et al., 2018) reports that the
belowground biomass in a bamboo forest accounts for 39.41\% of the total
plant biomass.. Another recent study (Zhang et al., 2019) shows that the
litter layer in bamboo forest plays a important role as phytOC storage.
In native steppes, plant aboveground biomass turns to litter in current
year, while the belowground biomass is huge and accumulated over
multiple years (Chai, et al., 2014; Dai, et al., 2012; Hou, et al.,
2014). Qi et al. (2016) shows that phytOC production from the
belowground part is much greater than that from the aboveground parts
for the typical steppe. The results of the present study confirms the
previous findings with more data from three steppe types along a
precitation gradient, and indicate the necessity to involve the
belowground part in the assessment of PhytOC production and
sequestration potential.

\textbf{5 CONCLUSIONS}

Our study focuses on the phytolith and PhytOC contents of different
plant communities and their constituent species on a climate gradient in
the semi-arid steppe region of the Mongolian Plateau. Our results show
that the phytolith and PhytOC contents differ among plant species, and
that climatic factors affect phytolith and PhytOC production rates of
steppe communities mainly through affecting plant production, whereas
their effects on the phytolith and PhytOC contents in plants are
relatively small. Our results also demonstrate that plant aboveground
biomass (AGB) and PhytOC content are strongly associated with the
current-year climate and bioavailable Si content in the soil, while the
variation in plant belowground biomass (BGB) and PhytOC content across
sites was more correlated with the long-term mean values of climatic and
soil factors across the sites, reflecting the perenniality of the
belowground part of steppe plants. More studies are warranted to
quantify annual PhytOC production from plant belowground part with the
effects of plant perenniality incorporated.

\textbf{ACKNOWLEDGEMENTS}

The work was supported by National Natural Science Foundation of China
(31670454), the Ministry of Science and Technology of China
(2015BAC02B04) and the Department of Science and Technology of Inner
Mongolia Autonomous Region (201501007).

\textbf{CONFLICT OF INTEREST}

None declared.

\textbf{AUTHOR CONTRIBUTIONS}

FYL and LQ conceptualized the study and designed the methodology; LQ,
TS, YG and XG did the field survey, sample collection and laboratory
analysis; LQ analyzed the data and wrote up the first manuscript with
inputs from FYL; all authors provided feedback and helped shape the
final manuscript.

\textbf{REFERENCES}

Bai, Y., Han, X., Wu, J., Chen, Z., \& Li, L. (2004). Ecosystem
stability and compensatory effects in the Inner Mongolia grassland.
Nature, 431, 181-184. https://doi.org/10.1038/nature02850

Bai, Y., Wu, J., Xing, Q., Pan, Q., Huang, J., Yang, D., \& Han, X.
(2008). Primary production and rain use efficiency across a
precipitation gradient on the Mongolia Plateau. Ecology, 89, 2140-2153.
https://doi.org/10.1890/07-0992.1

Bartoli, F., \& Wilding, L. P. (1980). Dissolution of biogenic opal as a
function of its physical and chemical properties. Soil Science Society
of America Journal, 44, 873-878.
https://doi.org/10.2136/sssaj1980.03615995004400040043x

Berner, R. A. (1992). Weathering, plants, and the long-term carbon
cycle. Geochimica et Cosmochimica Acta, 56, 3225-3231.
https://doi.org/10.1016/ 0016-7037 (92)9030-8

Blecker, S. W., Mcculley, R. L., Chadwick, O. A., \& Kelly, E. F.
(2006). Biologic cycling of silica across a grassland bioclimosequence.
Global Biogeochemical Cycles, 20, 1-11.
https://doi.org/10.1029/2006GB002690

Chai, X., Liang, C., Liang, M., Han, W., Li, Z. Y., Miao, B.,
\ldots{}Wang, L. (2014). Seasonal dynamics of belowground biomass and
productivity and potential of carbon sequestration in meadow steppe and
typical steppe in Inner Mongolia, China. Acta Ecologica Sinica, 34,
5530-5540. https://doi.org/10.584/ stxb201301190118

Chen, C., Huang, Z., Jiang, P., Chen, J., \& Wu, J. (2018). Belowground
phytolith- occluded carbon of monopodial bamboo in China: an overlooked
carbon stock. Frontiers in Plant Science, 6, 1615.
https://doi.org/10.3389/fpls.2018.01615

Clarkson, D. T., \& Hanson, J. B. (1980). The mineral nutrition of
higher plants. Annual Review of Plant Biology, 31, 239-298.
https://doi.org/10.1146/annurev.pp. 31.060180.001323

Conley, \& Daniel, J. (2002). Terrestrial ecosystems and the
biogeochemical silica cycle. Global Biogeochemical Cycles, 16,
68-1-68-8. https://doi.org/10.1029/ 2002GB001894

Dai, C., Kang, M., Ji, W., \& Jiang, Y. (2012). Responses of underground
productivity to biomass and environmental factors in Xilingol grassland,
Inner Mongolia. Chinese Journal of Grassland, 34, 54-60.
https://doi.org/1673-5021(2012) 03-0054-07

Easterling, D. R., Meehl, G. A., Parmesan, C., Changnon, S. A., Karl, T.
R., \& Mearns, L. O. (2000). Climate extremes: observations, modeling,
and impacts. Science, 298, 2068-2074.
https://doi.org/10.1126/science.289.5487.2068

Epstein, E. (1994). The anomaly of silicon in plant biology. Proceedings
of the National Academy of Sciences of the United States of America, 91,
11-17. https://doi.org/10.1073/pnas.91.1.11

Epstein, E. (2009). Silicon: its manifold roles in plants. Annals
Applied Biology, 155, 155-160.
https://doi.org/10.1111/j.1744-7348.2009.00343.x

Fraysse, F., Pokrovsky, O. S., Schott, J., \& Meunier, J. D. (2009).
Surface chemistry and reactivity of plant phytoliths in aqueous
solutions. Chemical Geology, 258, 197-206.
https://doi.org/10.1016/j.chemgeo.2008.10.003

Hodson, M. J., White, P. J., Mead, A., \& Broadley, M. R. (2005).
Phylogenetic variation in the silicon composition of plants. Annals of
Botany, 96, 1027-1046. https://doi.org/10.1093/aob/mci255

Hou, X., Ji, L., \& Wang, Z. (2014). Response of net primary
productivity and C accumulation of plant communities in desert steppe
and semiarid steppe with different land use types during two
hydrologically contrastiong growing seasons. Acta Ecologica Sinica, 34,
6256-6264. https://doi.org/10.5846/stxb201301310206

Ji, Z., Yang, X., Song, Z., Liu, H., Liu, X., Qiu, S., \ldots{}Zhang, X.
(2018). Silicon distribution in meadow steppe and typical steppe of
northern China and its implications for phytolith carbon sequestration.
Grass and Forage Science, 73, 482-492. https://doi.org/10.1111/gfs.12316

Jones, L. H. P., \& Milne, A. A. (1965). Studies of silica in the oat
plant. Plant and Soil, 23, 79-96. https://doi.org/10.1007/BF01347875

Knapp, A. K., \& Smith, M. D. (2001). Variation among biomes in temporal
dynamics of aboveground primary production. Science, 291, 481-484.
https://doi.org/ 10.1126/science.291.5503.481

Li, Z., Song, Z., Parr, J. F., \& Wang, H. (2013a). Occluded C in rice
phytoliths: implications to biogeochemical carbon sequestration. Plant
and Soil, 370, 615-623. https://doi.org/10.1007/s11104-013-1661-9

Li, Z., Song, Z., \& Li, B. (2013b). The production and accumulation of
phytolith-occluded carbon in Baiyangdian reed wetland of China. Applied
Geochemistry, 37, 117-124.
https://doi.org/10.1016/j.apgeochem.2013.07.012

Ma, J. F., \& Yamaji, N. (2006). Silicon uptake and accumulation in
higher plants. Trends in Plant Science, 11, 392-397.
https://doi.org/10.1016/j.tplants. 2006.06.007

Ma, W., Fang, J., Yang, Y., \& Mohammat, A. (2010). Biomass carbon
stocks and their changes in northern China's grasslands during
1982--2006. Science China-life Sciences, 53, 841-850.
https://doi.org/10.1007/s11427-010-4020-6

Pan, W., Song, Z., Liu, H., Mueller, K., Yang, X., Zhang, X.,
\ldots{}Wang, H. (2017). Impact of grassland degradation on soil
phytolith carbon sequestration in Inner Mongolia steppe of China.
Geoderma, 308, 86-92. https://doi.org/10.1016/ j.geoderma.2017.08.037

Parr, J. F., Sullivan, L. A., Chen, B., Ye, G., \& Zheng, W. (2010).
Carbon bio-sequestration within the phytoliths of economic bamboo
species. Global Change Biology, 16, 2661-2667.
https://doi.org/10.1111/j.1365-2486.2009. 02118.x

Parr, J. F., Sullivan, L. A., \& Quirk, R. (2009). Sugarcane phytoliths:
encapsulation and sequestration of a long-lived carbon fraction. Sugar
Tech, 11, 17-21. https:// doi.org/10.1007/s12355-009-0003-y

Parr, J. F., Dolic, V., Lancaster, G., \& Boyd, W. E. (2001). A
microwave digestion method for the extraction of phytoliths from
herbarium specimens. Review of Palaeobotany and Palynology, 116,
203-212. https://doi.org/10.1016/ S0034-6667(01)00089-6

Parr, J. F., \& Sullivan, L. A. (2005). Soil carbon sequestration in
phytoliths. Soil Biologyand Biochemistry, 37, 117-124.
https://doi.org/10.1016/ j.soilbio.2004.06.013

Parr, J. F., \& Sullivan, L. A. (2011). Phytolith occluded carbon and
silica variability in wheat cultivars. Plant and Soil, 342, 165-171.
https://doi.org/ 10.1007/s11104-010-0680-z

Parr, J. F., \& Sullivan, L. A. (2014). Comparison of two methods for
the isolation of phytolith occluded carbon from plant material. Plant
and Soil, 374, 45-53. https://doi.org/10.1007/s11104-013-1847-1

Qi, L., Li, F. Y., Huang, Z., Jiang, P., Baoyin, T., \& Wang, H. (2016).
Phytolith-occluded organic carbon as a mechanism for long-term carbon
sequestration in a typical steppe: the predominant role of belowground
productivity. Science of Total Environment, 577, 413-417.
https://doi.org/10.1016/j.scitotenv.2016.10.206

Ru, N., Yang, X., Song, Z., Liu, H., Hao, Q., Liu, X., \& Wu, X. (2018).
Phytoliths and phytolith carbon occlusion in aboveground vegetation of
sandy grasslands in eastern Inner Mongolia, China. Science of Total
Environment, 625, 1283-1289. https://
doi.org/10.1016/j.scitotenv.2018.01.055

Schaller, J., Brackhage, C., Paasch, S., Brunner, E., Baucker, E., \&
Dudel, E. G. (2013). Silica uptake from nanoparticles and silica
condensation state in different tissues of Phragmites australis. Science
of Total Environment, 442, 6-9.
https://doi.org/10.1016/j.scitotenv.2012.10.0166.199

Scurlock, J. M. O., \& Hall, D. O. (2010). The global carbon sink: a
grassland perspective. Global Change. Biology, 4, 229-233.
https://doi.org/10.1046/j.1365-2488.00151.x

Scurlock, J. M. O., Johnson, K. R., \& Olson, R. J. (2002). Estimating
net primary productivity from grassland biomass dynamics measurements.
Global Change Biology, 8, 736-753.
https://doi.org/10.1046/j.1365-2486.2002.00512.x

Song, Z., Liu, H., Stromberg, C. A. E., Yang, X., \& Zhang, X. (2017).
Phytolith carbon sequestration in global terrestrial biomes. Science of
Total Environment, 603, 502-509.
https://doi.org/10.1016/j.scitotenv.2017.06.107

Song, Z., Liu, H., Si, Y., \& Yin, Y. (2012a). The production of
phytoliths in China's grasslands: implications to the biogeochemical
sequestration of atmospheric CO\textsubscript{2}. Global Change Biology,
18, 3647-3653. https://doi.org/10.1111/gcb.12017

Song, Z., Wang, H., Strong, P. J., Li, Z., \& Jiang, P. (2012b). Plant
impact on the coupled terrestrial biogeochemical cycles of silicon and
carbon: implications for biogeochemical carbon sequestration.
Earth-Science Reviews, 115, 319-331.
https://doi.org/10.1016/j.earscirev.2012.09.006

Stromberg, C. A. E., Stilio, V. S. D., \& Song, Z. (2016). Functions of
phytoliths in vascular plants: an evolutionary perspective. Functional
Ecology, 30, 1286-1297. https://doi.org/10.1111/1365-2435.12692

Walkley, A. J., \& Black, I. A. (1934). An examination of the degtjareff
method for determining soil organic matter, and a proposed modification
of the chromic acid titration method. Soil Science, 37, 29-38.
https://doi.org/10.1097/ 00010694-193401000-00003

Yang, J., Li, Y., Huang, Z., Jiang, P., Xiang, T., \& Ying, Y. (2014).
Determination of phytolith-occluded carbon content using alkali
dissolution- spectrophotometry. Chinese Journal of Analytical Chemistry,
42, 1389-1390. https://doi.org/10.11895/j.issn.02533820.131190

Yang, X., Song, Z., Liu, H., Zwieten, L. V., Song, A. L., Li, Z.,
\ldots{}Wang, H. (2018). Phytolith accumulation in broadleaf and conifer
forests of northern China: implications for phytolith carbon
sequestration. Geoderma, 312, 36-44.
https://doi.org/10.1016/j.geoderma.2017.10.005

Zhang, X., Song, Z., Hao, Q., Wang, Y., Ding, F., \& Song, A. (2019).
Phytolith-occluded carbon storages in forest litter layers in southern
China: implications for evaluation of long-term forest carbon budget.
Frontiers in Plant Science, 10, 581. https://doi.org/10, 581. doi:
10.3389/fpls.2019.00581

Zuo, X., \& Lu, H. (2011). Carbon sequestration within millet phytoliths
from dry-farming of crops in China. Chin. Science Bulletin, 56,
3451-3456. https://doi.org/10.1007/s11434-011-4674-x

\textbf{FIGURE LEGENDS}

\textbf{FIG. 1.} The phytolith content in the above- and belowground
parts of dominant plants in the desert steppe (A), dry typical steppe
(B) and wet typical steppe (C) in Inner Mongolia. Species are ordered
according to their relative biomass in steppe communities. Different
lowercase letters indicate significant differences in the above- or the
belowground plant part among species (\emph{P} \textless{} 0.05).

\textbf{FIG. 2} .The PhytOC content in the above- and belowground parts
of dominant plants in the desert steppe (A), dry typical steppe (B) and
wet typical steppe (C) in Inner Mongolia. Species are ordered according
to their relative biomass in steppe communities. Different lowercase
letters indicate significant differences in the above- or the
belowground plant part among species (\emph{P} \textless{} 0.05).

\textbf{FIG. 3} . The phytolith content (A) and PhytOC content (B) in
the above- and belowground parts of steppe communities in Inner
Mongolia. No significant differences are detected for either above- or
belowground part among steppe types (\emph{P} \textless{} 0.05).

FIG.1.FIG.2.FIG.3

\textbf{TABLES}

\textbf{TABLE 1.} The soil bulk density (BD), moisture, pH, organic
carbon (SOC) and bioavailable Si contents at the three steppe sites\selectlanguage{english}
\begin{longtable}[]{@{}llllllll@{}}
\toprule
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Sites\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
BD (g cm\textsuperscript{-3})\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Moisture (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Moisture (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
pH\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
SOC (g kg\textsuperscript{-1})\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
SOC (g kg\textsuperscript{-1})\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Bioavailable Si (mg kg\textsuperscript{-1})\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
Desert steppe\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
1.30b\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2.79c\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
8.77a\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
8.77a\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
8.77a\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.90c\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.26a\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
Dry typical steppe\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
1.32b\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
14.71b\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
8.05a\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
8.05a\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
8.05a\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2.81b\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.32a\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
Wet typical steppe\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
1.49a\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
21.32a\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
7.51b\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
7.51b\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
7.51b\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
3.12a\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.27a\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

Note: different letters indicate significant difference among steppe
types at \emph{P} \textless{}0.05.

\textbf{TABLE2.} The aboveground (AGB) and belowground biomass (BGB) (kg
ha\textsuperscript{-1}; mean\selectlanguage{ngerman}±SE) of the three major steppe communities
and their major composing species in Inner Mongolia. (A/B refers to the
AGB/BGB ratio)\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
Types & Species name & AGB & BGB & A/B\tabularnewline
Desert steppe & \emph{Stipa klemenzii} & 256.89\selectlanguage{ngerman}±61.11 & 1511.11\selectlanguage{ngerman}±359.45 &
0.17\tabularnewline
& \emph{Cleistogenes songorica} & 83.00\selectlanguage{ngerman}±42.06 & 237.14\selectlanguage{ngerman}±120.17 &
0.35\tabularnewline
& \emph{Salsola collina} & 73.22\selectlanguage{ngerman}±58.74 & 95.09\selectlanguage{ngerman}±76.28 &
18.23\tabularnewline
& \emph{Scorzonera divaricata} & 21.67\selectlanguage{ngerman}±21.67 & 4.47\selectlanguage{ngerman}±4.47 &
4.85\tabularnewline
& \emph{Allium mongolicum} & 18.11\selectlanguage{ngerman}±8.71 & 95.32\selectlanguage{ngerman}±45.82 &
0.19\tabularnewline
& \emph{Caragana pygmaea} & 17.67\selectlanguage{ngerman}±15.71 & 0.97\selectlanguage{ngerman}±0.86 &
0.77\tabularnewline
& \emph{Carex korshinskyi} & 13.78\selectlanguage{ngerman}±2.41 & 52.99\selectlanguage{ngerman}±9.25 &
0.26\tabularnewline
& \emph{Allium bidentatum} & 8.44\selectlanguage{ngerman}±7.00 & 140.74\selectlanguage{ngerman}±116.64 &
0.06\tabularnewline
& \textbf{Sum of major species} & 492.78 & 2137.83\textsuperscript{\#}
&\tabularnewline
& \textbf{Community} & 562.27 & 4227.99\textsuperscript{\#}
&\tabularnewline
& \emph{Leymus chinensis} & 404.68\selectlanguage{ngerman}±40.26 & 586.49\selectlanguage{ngerman}±132.52 &
0.69\tabularnewline
& \emph{Stipa krylovii} & 394.12\selectlanguage{ngerman}±231.38 & 985.31\selectlanguage{ngerman}±227.18 &
0.40\tabularnewline
& \emph{Stipa grandis} & 352.92\selectlanguage{ngerman}±175.27 & 840.29\selectlanguage{ngerman}±163.22 &
0.42\tabularnewline
& \emph{Cleistogenes squarrosa} & 132.59\selectlanguage{ngerman}±62.40 & 301.34\selectlanguage{ngerman}±20.67 &
0.44\tabularnewline
& \emph{Agropyron michnoi} & 72.67\selectlanguage{ngerman}±72.67 & 117.20\selectlanguage{ngerman}±18.54 &
0.62\tabularnewline
& \emph{Carex korshinskyi} & 14.32\selectlanguage{ngerman}±14.32 & 95.48\selectlanguage{ngerman}±1.08 &
0.15\tabularnewline
& \emph{Artemisia frigida} & 7.16\selectlanguage{ngerman}±7.16 & 3.44\selectlanguage{ngerman}±0.66 & 2.08\tabularnewline
& \textbf{Sum of major species} & 1378.64 & 2929.55 &\tabularnewline
& \textbf{Community} & 1471.99 & 8639.89 &\tabularnewline
Wet typical steppe & \emph{Stipa grandis} & 553.48\selectlanguage{ngerman}±168.32 &
1777.45\selectlanguage{ngerman}±393.71 & 0.31\tabularnewline
& \emph{Cleistogenes squarrosa} & 303.37\selectlanguage{ngerman}±122.25 & 864.56\selectlanguage{ngerman}±316.41 &
0.33\tabularnewline
& \emph{Leymus chinensis} & 200.39\selectlanguage{ngerman}±83.52 & 301.21\selectlanguage{ngerman}±113.58 &
0.67\tabularnewline
& \textbf{Sum of major species} & 1057.24 & 2943.22 &\tabularnewline
& \textbf{Community} & 1120.09 & 8643.74 &\tabularnewline
\bottomrule
\end{longtable}

\textsuperscript{\#} The sum of the BGB of major species is the BGB in
top 20 cm soil layer determined in this study, while the BGB of
community is estimated based on the BGB in the top 20 cm soil layer and
the belowground biomass profile determined in previous studies for these
communities (Chai et al. 2014; Hou et al., 2014).

\textbf{TABLE 3.} Estimation of plant aboveground biomass (AGB) and net
primary productivity (ANPP), belowground biomass (BGB) and net primary
productivity (BNPP), and biomass-weighted community mean PhytOC content,
stock and production flux (mean \selectlanguage{ngerman}± SE) of the three steppe types in Inner
Mongolia.\selectlanguage{english}
\begin{longtable}[]{@{}lllllllll@{}}
\toprule
Steppe types & PhytOC content (g kg\textsuperscript{-1}) & PhytOC
content (g kg\textsuperscript{-1}) & AGB=ANPP & BGB & BNPP* & PhytOC
stock (kg ha\textsuperscript{-1}) & PhytOC stock (kg
ha\textsuperscript{-1}) & PhytOC production flux (kg
ha\textsuperscript{-1} yr\textsuperscript{-1})\tabularnewline
& aboveground & belowground & (kg ha\textsuperscript{-1}
yr\textsuperscript{-1}) & (0-70cm) & (kg ha\textsuperscript{-1}
yr\textsuperscript{-1}) & aboveground & belowground &
belowground\tabularnewline
Desert steppe & 0.68\selectlanguage{ngerman}±0.12a & 1.11\selectlanguage{ngerman}±0.26a & 562.65\selectlanguage{ngerman}±49.28b &
4227.99\selectlanguage{ngerman}±456.20b & 7964 & 0.38\selectlanguage{ngerman}±0.07b & 4.67\selectlanguage{ngerman}±0.16b & 9.18\tabularnewline
Dry typical steppe & 0.48\selectlanguage{ngerman}±0.01a & 0.72\selectlanguage{ngerman}±0.08a & 1471.99\selectlanguage{ngerman}±110.82a &
8639.89\selectlanguage{ngerman}±543.77a & 13446 & 0.71\selectlanguage{ngerman}±0.09a & 6.20\selectlanguage{ngerman}±0.23ab &
10.35\tabularnewline
Wet typical steppe & 0.59\selectlanguage{ngerman}±0.08a & 1.02\selectlanguage{ngerman}±0.07a & 1120.09\selectlanguage{ngerman}±52.98a &
8643.74\selectlanguage{ngerman}±491.55a & 17955 & 0.66\selectlanguage{ngerman}±0.01a & 8.79\selectlanguage{ngerman}±0.36a & 18.91\tabularnewline
\bottomrule
\end{longtable}

Note: The range of BNPP is estimated based on the BNPP and the turn-over
rate of belowground biomass determined in several studies on the
Mongolian steppes (Chai et al., 2014; Hou et al., 2014) and the
measurement of above- and belowground biomass (0-70 cm) in this
experiment. Different lowercase letters indicate significant differences
among steppe types at \emph{P} \textless{} 0.05 (Duncan's test).

\textbf{DATA AVAILABILITY STATEMENT}

Data will be available from the Dryad Digital Repository.

\textbf{Hosted file}

\verb`Figure.docx`  available at \url{https://authorea.com/users/346008/articles/472111-phytolith-occluded-carbon-sequestration-potential-in-three-major-steppe-types-along-a-precipitation-gradient-in-northern-china}

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