Introduction
Chemical structures of branched GDGTs and crenarchaeol.
Glycerol dialkyl glycerol tetraethers (GDGTs), membrane lipids of archaea
and certain bacteria, are widely distributed in marine and terrestrial
environments (Schouten et al., 2013). These lipids have
been a focus of attention of organic geochemists for more than 10 years
because they can be used to estimate environmental variables in the past
such as temperature, soil pH, organic carbon source and microbial community
structure (e.g., Schouten et al., 2002; Hopmans et al., 2004; Weijers et
al., 2006; Lipp et al., 2008; Kim et al., 2010; Peterse et al., 2012; Zhu et
al., 2016). There are generally two types of GDGTs, isoprenoid (iGDGTs) and
non-isoprenoid, branched GDGTs (brGDGTs; Fig. 1). The former group is more
abundant in aquatic settings, and generally thought to be produced by
Thaumarchaeota, a specific genetic cluster of the archaea domain
(Sinninghe Damsté et al., 2002; Schouten et al., 2008), although
Euryarchaeota may be a significant source of iGDGTs in the ocean
(e.g., Lincoln et al., 2014). In contrast, the
1,2-di-O-alkyl-sn-glycerol configuration of brGDGTs was interpreted as evidence
for a bacterial rather than archaeal origin for brGDGTs (Sinninghe
Damsté et al., 2000; Weijers et al., 2006). So far, only one brGDGT with
two 13,16-dimethyl octacosanyl moieties was unambiguously detected in two
species of Acidobacteria (Sinninghe Damsté et al.,
2011), which hardly explains high diversity and ubiquitous occurrence of up
to 15 brGDGT isomers in environments (Weijers et al., 2007b; De Jonge et
al., 2014). Therefore, other biological sources of brGDGTs, although not yet
identified, are likely.
The source difference between brGDGTs and iGDGTs led researchers to
develop a branched and isoprenoid tetraether (BIT) index, expressed as
the relative abundance of terrestrial-derived brGDGTs to aquatic-derived
Thaumarchaeotal (Hopmans et al., 2004). Subsequent
studies found that the BIT index is specific to soil organic carbon because
GDGTs are absent in vegetation (e.g., Walsh et al., 2008; Sparkes et al.,
2015). The BIT index is generally higher than 0.9 in soils, but close to 0
in marine sediments devoid of terrestrial inputs (Weijers et al., 2006, 2014). Since its advent, the BIT index has been increasingly
used to trace soil organic matter in different environments (e.g.,
Herfort et al., 2006; Kim et al., 2006; Blaga et al., 2011; Loomis et al.,
2011; Wu et al., 2013). However, the BIT index is not just dependent on the
abundance of brGDGTs, which reflects the input of soil organic matter, but
also on the abundance of crenarchaeol, which is linked to marine
productivity (e.g., Herfort et al., 2006; Smith et al, 2012; Fietz et al.,
2012). Besides the BIT index, Weijers et al. (2007b) found that
the number of cyclopentane moieties of brGDGTs, expressed as the cyclization of
branched tetraethers (CBT), correlated negatively with soil pH, while the
number of methyl branches of brGDGTs, expressed as the methylation of branched
tetraethers (MBT), was dependent on annual mean air temperature (MAT) and to
a lesser extent on soil pH. The MBT/CBT proxies were further corroborated by
subsequent studies (e.g., Sinninghe Damsté et al., 2008; Peterse et
al., 2012; Yang et al., 2014a). Assuming that brGDGTs preserved in marine
sediments close to the Congo River outflow were derived from soils in the
river catchment, Weijers et al. (2007a) reconstructed large-scale
continental temperature changes in tropical Africa that span the past 25 000 years by
using the MBT/CBT proxy. Recently, De Jonge et al. (2013) used tandem high-performance liquid
chromatography–mass spectrometry (2-D HPLC-MS) and identified a series of
novel 6-methyl brGDGTs, which were previously coeluted with 5-methyl brGDGTs.
This finding resulted in the redefinition and recalibration of brGDGTs'
indices (e.g., De Jonge et al., 2014; Xiao et al., 2015).
One underlying assumption of all brGDGT-based parameters is their source
specificity; i.e., brGDGTs are only biosynthesized by bacteria thriving in
soils and peat. Several studies, however, observed different brGDGT
compositions between marine sediments and soils on adjacent lands,
supporting in situ production of brGDGTs in marine environments (e.g.,
Peterse et al., 2009a; Zhu et al., 2011; Liu et al., 2014; Weijers et al.,
2014; Zell et al., 2014), analogous to lacustrine settings (e.g.,
Sinninghe Damsté et al., 2009; Tierney and Russell, 2009; Tierney et
al., 2012) and rivers (e.g., Zhu et al., 2011; De Jonge et al., 2015;
French et al., 2015; Zell et al., 2015). Peterse et al. (2009a) compared the
brGDGTs' distribution in Svalbard soils and nearby fjord sediments, and
found that concentrations of brGDGTs (0.01–0.20 µg g-1 dw) in fjord
sediments increased towards the open ocean and the distribution was
strikingly different from that in soil. Zhu et al. (2011) examined
distributions of GDGTs in surface sediments across a Yangtze River-dominated
continental margin, and found evidence for production of brGDGTs in the oxic
East China Sea shelf water column and the anoxic sediments/waters of the
Lower Yangtze River. At the global scale, Fietz et al. (2012) reported a significant correlation between
concentrations of brGDGTs and crenarchaeol (p < 0.01; R2= 0.57–0.99), suggesting that a common or mixed source for brGDGTs and iGDGTs
are actually commonplace in lacustrine and marine settings. More recently,
Sinninghe Damsté (2016) reported tetraethers in surface
sediments from 43 stations in the Berau River delta (Kalimantan, Indonesia),
and this result, combined with data from other shelf systems, is coherent
with the hypothesis that brGDGTs are produced in situ in shelf sediments,
especially at water depth of 50–300 m.
Location of the samples used in this study. White circles and black
circles indicate the soils and marine sediments, respectively. Red crosses
denote three sediment cores (M1, M3 and M7) in the Bohai Sea. YR is the
Yellow River.
Fluvial inputs and wind are the most important pathways for transporting
terrestrial material into sea. On the continental shelf, fluvial discharge
is more important than atmospheric input because brGDGTs are either below
the detection level (Hopmans et al., 2004) or present
at low abundance (Fietz et al., 2013; Weijers et al., 2014). In the
remote ocean where no direct impact from land erosion via rivers takes
place, eolian transport and in situ production are major contributors to
brGDGTs. Weijers et al. (2014) found that distributions of
African dust-derived brGDGTs were similar to those of soils but different
from those of distal marine sediments, providing a possibility to
distinguish terrestrial vs. marine brGDGTs based on molecular compositions.
However, so far no robust molecular indicator is available for estimating
the source of brGDGTs in marine environments. Considering this, we conduct a
detailed study on GDGTs in three cores from the Bohai Sea, which are subject
to the Yellow River influence to a different degree. Our purpose is to
evaluate the source-discerning capability of different brGDGT parameters,
from which the most sensitive parameter is selected and applied for globally
distributed marine sediments and soils to test whether it is valid at the
global scale. Our study supplies an important step for improving accuracy of
brGDGT-derived proxies and better understanding the marine carbon cycle and
paleoenvironments.
Material and methods
Study area and sampling
The Bohai Sea is a semi-enclosed shallow sea in northern China, extending
about 550 km from north to south and about 350 km from east to west. Its
area is 77 000 km2, and the mean depth is 18 m (Hu et
al., 2009). The Bohai Strait at the eastern portion is the only passage
connecting the Bohai Sea to the outer Yellow Sea. Several rivers, including
the Yellow River, the second largest river in the world in terms of sediment
load (Milliman and Meade, 1983), drain into the Bohai Sea with a
total annual runoff of 890 × 108 m3. A gravity
core 64 cm long (M1; 37.52∘ N, 119.32∘ E) was collected in July
2011, while two other cores, M3 (38.66∘ N, 119.54∘ E; 53 cm long)
and M7 (39.53∘ N, 120.46∘ E; 60 cm long), were
collected in July 2013 (Fig. 2). The sites M1, M3 and M7 are located in the
south, the center and the north of the Bohai Sea, respectively. The cores
were transported to the lab where they were sectioned at 1 or 2 cm interval.
The age model was established on the basis of 210Pb and 137Cs
activity, showing that the bottom sediments are less than 100 years old
(Wu et al., 2013 and unpublished data).
Lipid extraction and analyses
The detailed procedures for lipid extraction and GDGT analyses have been
described in previous studies (Ding et al., 2015; Xiao et al., 2015).
Briefly, the homogenous freeze-dried samples were ultrasonically extracted
with dichloromethane (DCM)/methanol (3:1 v:v). The extracts were separated
into nonpolar and polar fractions over silica gel columns. The latter
fraction containing GDGTs was analyzed using an Agilent 1200
HPLC–atmospheric pressure chemical ionization–triple quadruple mass
spectrometry (HPLC–APCI–MS) system. The separation of 5- and 6-methyl
brGDGTs was achieved with two silica columns in sequence (150 mm × 2.1 mm; 1.9 µm, Thermo Finnigan; USA). The quantification was achieved
by comparison of the respective protonated ion peak areas of each GDGT to
the internal standard (C46 GDGT) in selected ion monitoring (SIM) mode.
The protonated ions were m/z 1050, 1048, 1046, 1036, 1034, 1032, 1022,
1020 and 1018 for brGDGTs, 1302, 1300, 1298, 1296 and 1292 for iGDGTs and 744 for
C46 GDGT.
Parameter calculation and statistics
The BIT, MBT, methyl index (MI), degree of cyclization (DC) of brGDGTs and
the weighted average number of cyclopentane moieties for tetramethylated brGDGTs
(no. ringstetra) were calculated according to the definitions of
Hopmans et al. (2004), Weijers et al. (2007b), Zhang et al. (2011), Sinninghe
Damsté et al. (2009) and Sinninghe Damsté (2016), respectively.
BIT=Ia+IIa+IIIaIa+IIa+IIIa+IVMBT=Ia+Ib+IcIa+IIa+IIIa+Ib+IIb+IIIb+Ic+IIc+IIIcMI=4×Ia+Ib+Ic+5×IIa+IIb+IIb+6×IIIa+IIIb+IIIcDC=Ib+IIbIa+IIa+Ib+IIbno.ringstetra=Ib+2×IcIa+Ib+Ic,
where roman numbers denote relative abundance of compounds depicted in Fig. 1. In this study, we used two silica LC columns in tandem and successfully
separated 5- and 6-methyl brGDGTs. However, many previous studies
(e.g., Weijers et al., 2006) used one LC column, and
did not separate 5- and 6-methyl brGDGTs. Considering this, we combined
5-methyl and 6-methyl brGDGT as one compound in this study; for example,
IIIa denotes the total abundance of brGDGT IIIa and IIIa' in Fig. 1.
An analysis of variance (ANOVA) was conducted for different types of samples
to determine whether they differ significantly from each other. The SPSS 16.0
software package (IBM, USA) was used for the statistical analysis. Squared
Pearson correlation coefficients (R2) were reported, and the significance
level is p < 0.05.
Parameters including brGDGTs IIIa / IIa, Ia / IIa, the BIT index, MBT,
MI, DC, percentages of tetra-, penta- and hexa-methylated brGDGTs and the
weighted average number of cyclopentane moieties (no. rings for
tetramethylated brGDGTs) based on the GDGTs from three cores (M1, M3 and M7;
see Fig. 2) in the Bohai Sea. Different letters in parentheses (a, b, c,
d) represent significant difference at the level of p < 0.05.
Indexes
Soil
M1
M3
M7
IIIa / IIa
0.39 ± 0.25 (a)
0.63 ± 0.06 (b)
1.16 ± 0.12 (c)
0.93 ± 0.07 (d)
Ia / IIa
4.93 ± 9.60 (a)
0.59 ± 0.07 (b)
0.81 ± 0.06 (b)
0.91 ± 0.05 (b)
BIT
0.75 ± 0.22 (a)
0.50 ± 0.19 (b)
0.14 ± 0.06 (c)
0.11 ± 0.03 (c)
MBT
0.45 ± 0.30 (a)
0.32 ± 0.03 (b)
0.33 ± 0.01 (b)
0.38 ± 0.01 (ab)
MI
4.70 ± 0.42 (a)
4.88 ± 0.05 (b)
4.91 ± 0.03 (b)
4.81 ± 0.02 (ab)
DC
0.31 ± 0.21 (a)
0.62 ± 0.03 (b)
0.79 ± 0.03 (c)
0.82 ± 0.02 (c)
%tetra
0.45 ± 0.30 (a)
0.32 ± 0.03 (b)
0.33 ± 0.01 (c)
0.38 ± 0.01 (c)
%hexa
0.16 ± 0.12 (a)
0.20 ± 0.02 (b)
0.24 ± 0.02 (b)
0.20 ± 0.01 (b)
%penta
0.39 ± 0.20 (a)
0.48 ± 0.02 (b)
0.44 ± 0.02 (b)
0.42 ± 0.01 (b)
No. ringstera
0.20 ± 0.15 (a)
0.39 ± 0.03 (b)
0.47 ± 0.02 (c)
0.47 ± 0.02 (c)
Data compilation of global soils and marine sediments
The dataset in this study is composed of relative abundance of GDGTs and
derived parameters from 1354 globally distributed soils and 589 marine
sediments (Fig. 2 and Supplement). These sampling sites span a wide
area from 75.00∘ S to 79.28∘ N and 168.08∘ W to
174.40∘ E, and the water depth ranges from 1.0 to 5521 m. The marine samples are from
the South China Sea (Hu et al., 2012; Jia et al., 2012; O'Brien et al.,
2014; Dong et al., 2015), the Caribbean Sea (O'Brien et al., 2014),
the western equatorial Pacific Ocean (O'Brien et al., 2014), the southeast
Pacific Ocean (Kaiser et al., 2015), the Chukchi and
Alaskan Beaufort seas (Belicka and Harvey, 2009), the eastern Indian
Ocean (Chen et al., 2014), the East Siberian Arctic Shelf
(Sparkes et al., 2015), the Kara Sea (De Jonge et al., 2015, 2016), Svalbard fjord (Peterse et
al., 2009a), the Red Sea (Trommer et al., 2009), the southern Adriatic
Sea (Leider et al., 2010), the Columbia estuary
(French et al., 2015), globally distributed distal
marine sediments (Weijers et al., 2014) and the Bohai Sea
(this study). Soil samples are from Svalbard (Peterse et
al., 2009b), Columbia (French et al., 2015), China
(Yang et al., 2013, 2014a, b; Ding et al.,
2015; Xiao et al., 2015; Hu et al., 2016), California geothermal
(Peterse et al., 2009b), France and Brazil
(Huguet et al., 2010), western Uganda (Loomis et
al., 2011), the USA (Tierney et al., 2012), Tanzania
(Coffinet et al., 2014), Indonesia, Vietnam, the Philippines, China and
Italy (Mueller-Niggemann et al., 2016) as well as globally
distributed soils (Weijers et al., 2006; Peterse et al., 2012; De Jonge
et al., 2014).
Averaged percentages of individual brGDGTs in soils (a), core M1 (b), M3 (c) and M7 (d).
The soil data are from Yang et al. (2014a).
Results and discussion
Distribution and source of brGDGTs in Bohai Sea
A series of iGDGTs including crenarchaeol and brGDGTs including 5-methyl and
6-methyl isomers were detected in Bohai Sea sediments. For brGDGTs, a total
of 15 compounds were identified including three tetramethylated brGDGTs (Ia,
Ib and Ic), six pentamethylated brGDGTs (IIa, IIb, IIc, IIa', IIb' and IIc')
and six hexamethylated brGDGTs (IIIa, IIIb, IIIc, IIIa', IIIb' and IIIc').
In order to evaluate provenances of brGDGTs, we calculated various
parameters including the BIT index, percentages of tetra-, penta- and
hexa-methylated brGDGTs, no. rings for tetramethylated brGDGTs, DC, MI, MBT,
brGDGTs IIIa / IIa and Ia / IIa (Table 1). The values of the BIT index ranged
from 0.27 to 0.76 in the core M1, which are much higher than that in the
core M3 (0.04–0.25) and the core M7 (0.04–0.18). Such a difference is not
surprising because the site M1 is closest to the Yellow River outflow, and it
receives more terrestrial organic carbon than the other (Fig. 2). However,
the BIT index itself has no ability to determine the source of brGDGTs
(terrestrial vs. aquatic) because brGDGTs and crenarchaeol used in this
index are thought to be specific to soil organic carbon and marine organic
carbon, respectively (Hopmans et al., 2004), although
crenarchaeol is also present in soils at low abundance
(Weijers et al., 2006). For individual brGDGTs, the core
M1 is characterized by significantly higher percentage of brGDGT IIa
(28 ± 1 %) than the core M2 (18 ± 1 %) and the core M3
(18 ± 0 %; Fig. 3). We performed ANOVA for a variety of brGDGTs'
parameters. All results except from MI show a significant difference between
Chinese soils and Bohai Sea sediments. The IIIa / IIa ratio is the most
sensitive parameter which can completely separate the samples into four
groups: Chinese soils (0.39 ± 0.25; mean ± standard deviation; same hereafter), M1
sediments (0.63 ± 0.06), M3 sediments (1.16 ± 0.12) and M7
sediments (0.93 ± 0.07).
(a) The relationship between brGDGT IIIa / IIa ratio and the BIT index
of samples from Peterse et al. (2009a); (b) histograms of
brGDGT IIIa / IIa ratio of the core lipids (CLs) and intact polar lipids
(IPLs) in samples from De Jonge et al. (2015); (c) the
relationship between brGDGT IIIa / IIa ratio and the BIT index in samples from
Sparkes et al. (2015); (d) the relationship between
brGDGT IIIa / IIa ratio and distance from the river mouth in samples from Sparkes
et al. (2015).
Three factors may account for the occurrence of higher IIIa / IIa ratio in the
Bohai Sea sediments than Chinese soils: selective degradation during land to
sea transport, admixture of river produced brGDGTs and in situ production of
brGDGTs in sea. Huguet et al. (2008, 2009) reported that iGDGTs (i.e.,
crenarchaeol) were degraded at a rate 2-fold higher than soil-derived
brGDGTs under long-term oxygen exposure in the Madeira Abyssal Plain,
leading to increase of the BIT index. Such selective degradation, however,
cannot explain the significantly different IIIa / IIa ratios between the Chinese
soils and Bohai Sea sediments because unlike crenarchaeol, both IIIa and IIa
belong to brGDGTs with similar chemical structures, and thus have similar
degradation rates. In situ production of brGDGTs in rivers is a widespread
phenomenon, and can change brGDGTs' composition in sea when they are
transported there (e.g., Zhu et al., 2011; De Jonge et al., 2015; Zell et
al., 2015). However, the study along the lower Yellow River–estuary–coast
transect suggests that brGDGTs in surface sediments are primarily of land
origin (Wu et al., 2014). In our study, the site M1 is
adjacent to the Yellow River mouth, and receives the largest amount of
terrestrial organic matter, causing lower IIIa / IIa values (0.63 ± 0.06). In contrast, the site M3 located in central Bohai Sea comprises the
least amount of terrestrial organic matter, resulting in higher IIIa / IIa
values (1.16 ± 0.12). The intermediate IIIa / IIa values at the site M7
(0.93 ± 0.07) is attributed to moderate land erosion nearby the northern
Bohai Sea (Fig. 2). These GDGTs' results, consistent with other terrestrial
biomarkers such as C29 and C31 n alkanes and C29 sterol (data
not showed here), suggest that the higher IIIa / IIa values in the Bohai Sea
sediments compared to Chinese soils (0.39 ± 0.25) are most likely caused
by in situ production of brGDGTs.
Global distribution pattern of brGDGT IIIa / IIa ratio in soils and
marine sediments.
Regional and global validation of brGDGT IIIa / IIa
To test whether the IIIa / IIa ratio is valid in other environments, we apply
it to the dataset for Svalbard (Peterse et al., 2009a),
the Yenisei River outflow (De Jonge et al., 2015) and
the East Siberian Arctic Shelf (Sparkes et al., 2015).
Similar to Bohai Sea in this study, the compounds brGDGT IIa and IIIa are
also ubiquitously present in these environments. By comparing the
compositions of brGDGTs in Svalbard soils and nearby fjord sediments,
Peterse et al. (2009a) indicated that sedimentary organic
matter in fjords was predominantly from marine origin. A plot of BIT vs.
IIIa / IIa (Fig. 4a) clearly grouped the samples into two groups, which
correspond to soils (> 0.75 for BIT and < 1.0 for
IIIa / IIa) and marine sediments (< 0.3 for BIT and > 1.0
for IIIa / IIa). Another line of evidence is from De
Jonge et al. (2015) who examined brGDGTs in core lipids (CLs) and intact
polar lipids (IPLs) in the Yenisei River outflow. As the IPLs are rapidly
degraded in the environment, they can be used to trace living or recently
living material, while the CLs are generated via degradation of the IPLs
after cell death (White et al., 1979; Lipp et al., 2008). The compilation
of brGDGTs' abundance from De Jonge et al. (2015) shows
significant difference of the IIIa / IIa ratio between the IPL fractions
(> 1.0) and CL fractions (< 0.8; Fig. 4b). Such disparity
supports the hypothesis that brGDGTs produced in marine environments have higher IIIa / IIa
values because labile intact polar brGDGTs are mainly produced in situ,
whereas recalcitrant core brGDGTs are composed of more allochthonous
terrestrial components. Sparkes et al. (2015) examined
brGDGTs in surface sediments across the East Siberian Arctic Shelf (ESAS)
including the Dmitry Laptev Strait, Buor-Khaya Bay, ESAS nearshore and ESAS
offshore. The plot of BIT vs. IIIa / IIa again results in two groups, one
group with lower BIT values (< 0.3) and higher IIIa / IIa values
(0.8–2.3), mainly from ESAS offshore, and another group with higher BIT
values (0.3–1.0) and lower IIIa / IIa values (0.4–0.9), from the Dmitry-Laptev
Strait, Buor-Khaya Bay and ESAS nearshore (Fig. 4c). A strong linear
correlation was observed between the IIIa / IIa ratio and the distance from
the river mouth (R2= 0.58; p < 0.05; Fig. 4d), in accordance with the
data of the BIT index and δ13Corg (Sparkes et al., 2015). All lines of evidence
support the concept that marine-derived brGDGTs have higher IIIa / IIa values than
terrestrial-derived brGDGTs.
We further extend the dataset for global scale (Fig. 5), showing that the
IIIa / IIa ratio is still significantly higher in marine sediments than soils
(p < 0.01). An exception was observed for Red Sea sediments, which have
unusually low IIIa / IIa values (0.39 ± 0.21) compared to other marine
sediments (> 0.87). The Red Sea has a restricted connection to
the Indian Ocean via the Bab el Mandeb Strait. This, combined with high
insolation, low precipitation and strong winds results in surface water
salinity up to 41 PSU in the south and 36 PSU in the north of the Red Sea
(Sofianos et al., 2002). Under such an extreme
environment, distinct microbial populations may develop and produce GDGTs
different from those in other marine settings (see Trommer et al.,
2009 for details).
Overall, the global distribution of IIIa / IIa shows the highest values in
many deep sea sediments (2.6–5.1), the lowest values in soils (< 1.0), and intermediate values in sediments from bays, coastal areas or
marginal seas (0.87–2.62; Fig. 5). These results are consistent with our
data from the Bohai Sea, and confirm that the IIIa / IIa ratio is a useful
proxy for tracing the source of brGDGTs in marine sediments at regional and
global scales.
A plot showing a positive correlation between soil pH and IIIa / IIa.
The data are from Peterse et al. (2012) and this study.
Relationship between the IIIa / IIa ratio and the BIT index of
globally distributed samples: soils (orange circle) and marine sediments
(red circle). Dashed lines represent lower or upper threshold values for
90 % of soils/sediments.
Why do marine sediments generally have higher IIIa / IIa values than soils? It
has been reported that the relative of methyl groups positively correlates
with soil pH and negatively correlates with MAT (Weijers et al., 2007b;
Peterse et al., 2012). The IIIa / IIa ratio is actually an abundance ratio of
hexamethylated to pentamethylated brGDGT, and thus is also affected by
ambient temperature and pH. Unlike iGDGTs, which are well known to be mainly
produced by Thaumarchaeota (Sinninghe Damsté et al., 2002; Schouten
et al., 2008), the marine source of brGDGTs remains elusive. Here, we assume
that marine organisms producing brGDGTs respond to ambient temperature in
the same way as the brGDGTs producing soil bacteria, i.e., a negative
correlation between relative number of methyl group of brGDGTs and ambient
temperature. Because a large temperature gradient exists from surface to
bottom water in the ocean, we need to consider the location where brGDGTs are
produced. If brGDGTs in marine environments are predominantly produced in
the euphotic zone, we would not observe a significant difference for the
IIIa / IIa ratio between land and sea because both soils and marine sediments
are globally distributed, leading to no systematic difference between soil
temperature and sea surface temperature. Alternatively, if brGDGTs in marine
sediments are partially derived from deep-water dwelling or benthic
organisms, cold deep water (generally 1–2 ∘C) would cause higher
IIIa / IIa values in marine sediments, as we observed in this study. However,
to the best of our knowledge, there is no study reporting in situ production
of brGDGTs throughout the water column in ocean. Recent studies (Taylor
et al., 2013; Kim et al., 2015) have suggested that Thaumarchaeota are thriving
in the deeper, bathypelagic water column (> 1000 m water depth)
biosynthesized iGDGTs with different compositions to surface-dwelling
Thaumarchaeota, and thereby alter signals of TEX86 in sediments.
Besides temperature, pH can also alter compositions of brGDGTs (Weijers et
al., 2007). Based on global soil data, the IIIa / IIa ratio shows a strong
positive correlation with soil pH (R2= 0.51; Fig. 6). In our study,
the majority of soils are acidic or neutral (pH < 7.3), and only 8 %
of soil samples mainly from semi-arid and arid regions have a pH of
> 8.0 (e.g., Yang et al., 2014a). In
contrast, seawater is constantly alkaline, with a mean pH of 8.2. With this
systematic difference, bacteria living in soils tend to produce higher
proportions of brGDGT IIa, whereas unknown marine organisms tend to
biosynthesize higher proportions of brGDGT IIIa if they respond to ambient
pH in a similar way as soil bacteria in terms of biosynthesis of brGDGTs. It
should be pointed out that unlike fairly stable pH of overlying seawater,
the pH of porewaters in marine sediments can vary significantly, which may
influence compositions of brGDGTs. Nevertheless, at the current stage, the
occurrence of higher IIIa / IIa values in marine sediments is most likely
attributed to the relative higher pH and lower water temperature. Further
studies are needed to disentangle the relative importance of these two factors.
Percentage of soil organic carbon (%OCsoil) or terrestrial
organic carbon (%OCterr) based on a binary mixing model of BIT (a),
δ13Corg (b) and IIIa / IIa (c) for the East Siberian Arctic
Shelf (Sparkes et al., 2015).
Implication of IIIa / IIa on other brGDGT proxies
Because brGDGTs can be produced in marine settings, they are no longer
specific to soil organic matter, which inevitably affects brGDGT proxies
(e.g., BIT, MBT/CBT). The plot of BIT vs. IIIa / IIa on the basis of the global
dataset shows that the IIIa / IIa ratio has a value of < 0.59 for
90 % of soil samples and > 0.92 for 90 % of marine sediments
(Fig. 7). Considering this fact, we propose that the IIIa / IIa ratio of
< 0.59 and > 0.92 represents terrestrial (or soil) and
marine endmembers, respectively. The BIT index has a value of
> 0.67 for 90 % of soils and < 0.16 for 90 % of
marine sediments (Fig. 7). Overall, the BIT index decreased with increasing
IIIa / IIa values (BIT=1.08×0.28IIIaIIa-0.03;R2=0.77; Fig. 7),
suggesting that both the IIIa / IIa and BIT are useful indexes for
assessing soil organic carbon in marine settings. However, when the BIT
index has an intermediate value (i.e., 0.16 to 0.67), it is not valid to
determine the provenance of brGDGTs. For example, several marine samples
with BIT values of ∼ 0.35 show a large range of IIIa / IIa
(0.4 to 2.4; Fig. 7), suggesting that the source of brGDGTs can vary case by
case. In this situation, the measurement of the IIIa / IIa ratio is
strongly recommended.
The different IIIa / IIa values between land and marine endmembers may
provide an approach to quantify the contribution of soil organic carbon in
marine sediments. Similar to the BIT index, we used a binary mixing model to
calculate percentage of soil organic carbon (%OCsoil) as follows:
%OCsoil=[IIIa/IIa]sample-[IIIa/IIa]marine[IIIa/IIa]soil-[IIIa/IIa]marine×100,
where [IIIa / IIa]sample, [IIIa / IIa]soil and [IIIa / IIa]marine
are the abundance ratio of brGDGT IIIa / IIa for samples, soils and marine
sediments devoid of terrestrial influences, respectively.
We applied this binary mixing model to the East Siberian Arctic Shelf
because the data of BIT, δ13Corg and distance from the river
mouth are all available (Sparkes et al., 2015). With
the distance from the river mouth increasing from 25 to > 700 km, the
BIT, IIIa / IIa and δ13Corg change from 0.95 to 0, 0.53 to
2.21 and -27.4 to -21.2 ‰,
respectively, reflecting the spatial variability of sedimentary organic carbon
sources. For the BIT index, we used 0.97 and 0.01 as terrestrial and marine
endmember values based on previous studies for Arctic surrounding regions
(De Jonge et al., 2014; Peterse et al., 2014), which are similar to
global average values (Hopmans et al., 2004). For
δ13Corg, we chose -27 and -20 ‰ as C3 terrestrial and marine organic carbon
endmembers (Meyers, 1997). For the IIIa / IIa ratio, we used a global
average value of marine sediments (1.6) and soils (0.24), respectively,
based on this study. By applying these endmember values in Eq. (6), we
calculated the percentage of soil organic carbon (%OCsoil). We removed a
few data points if their calculated %OCsoil values were greater than
100 or below 0 %. It should be noted that the endmember value will
affect quantitative results, but does not change a general trend of
%OCsoil. The results based on all three parameters show a decreasing
trend seawards (Fig. 8). However, the %OCsoil based on δ13Corg is the highest (75 ± 18 %), followed by that from
the IIIa / IIa ratio (58 ± 15 %) and then that from the BIT index
(43 ± 27 %). This difference has been explained by the fact that δ13Corg is a bulk proxy for marine vs. terrestrial influence of
sedimentary organic carbon (SOC), whereas the BIT index is for a portion of
the bulk SOC, i.e., soil OC (Walsh et al., 2008) or
fluvial OC (Sparkes et al., 2015). For the estimated
%OCsoil, δ13Corg presents a stronger positive
correlation with the IIIa / IIa ratio (R2= 0.49) than the BIT index
(R2= 0.45), suggesting that the IIIa / IIa ratio may serve as a better
proxy for quantifying soil organic carbon than the BIT index because it is
less affected by selective degradation of branched vs. isoprenoid GDGTs and
high production of crenarchaea in marine environments (Smith et al.,
2012).