BGBiogeosciencesBGBiogeosciences1726-4189Copernicus PublicationsGöttingen, Germany10.5194/bg-13-147-2016Insights into the transfer of silicon isotopes into the sediment recordPanizzoV. N.virginia.panizzo@nottingham.ac.ukSwannG. E. A.https://orcid.org/0000-0002-4750-9504MackayA. W.https://orcid.org/0000-0002-6328-769XVologinaE.SturmM.PashleyV.HorstwoodM. S. A.School of Geography, Centre for Environmental Geochemistry, University of Nottingham, University Park, Nottingham, NG7 2RD, UKCentre for Environmental Geochemistry, British Geological Survey, Keyworth, Nottingham, NG12 5GG, UKEnvironmental Change Research Centre, Department of Geography, University College London, Gower Street, London, WC1E 6BT, UKInstitute of Earth's Crust, Siberian Branch of the Russian Academy of Sciences, 128 ul. Lermontov, Irkutsk, 664033, RussiaEawag-ETH, Swiss Federal Instiute of Aquatic Science and Technology, 8600, Dübendorf, SwitzerlandNERC Isotope Geosciences Laboratory, British Geological Survey, Keyworth, Nottingham, NG12 5GG, UKV. N. Panizzo (virginia.panizzo@nottingham.ac.uk)15January201613114715722May201523June20159December201510December2015This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://bg.copernicus.org/articles/13/147/2016/bg-13-147-2016.htmlThe full text article is available as a PDF file from https://bg.copernicus.org/articles/13/147/2016/bg-13-147-2016.pdf
The first δ30Sidiatom data from lacustrine sediment
traps are presented from Lake Baikal, Siberia. Data are compared with
March surface water (upper 180 m) δ30SiDSi
compositions for which a mean value of +2.28‰± 0.09
(95 % confidence) is derived. This value acts as the pre-diatom
bloom baseline silicic acid isotopic composition of waters
(δ30SiDSi initial). Open traps were deployed along
the depth of the Lake Baikal south basin water column between
2012 and 2013. Diatom assemblages display a dominance (>85 %) of
the spring/summer bloom species Synedra acus var radians, so that
δ30Sidiatom compositions reflect predominantly spring/summer bloom
utilisation. Diatoms were isolated from open traps and, in addition,
from 3-monthly (sequencing) traps (May, July and August 2012) for
δ30Sidiatom analyses. Mean
δ30Sidiatom values for open traps are
+1.23‰± 0.06 (at 95 % confidence and MSWD of 2.9,
n=10).
Total dry mass sediment fluxes are highest in June 2012, which we attribute to the
initial export of the dominant spring diatom bloom. We therefore argue that May
δ30Sidiatom signatures (+0.67‰± 0.06,2σ) when compared
with mean upper water δ30SiDSi initial (e.g. pre-bloom) signatures
can be used to provide a snapshot estimation of diatom uptake fractionation factors
(ϵuptake) in Lake Baikal. A ϵuptake estimation of -1.61 ‰ is
therefore derived, although we emphasise that synchronous monthly δ30SiDSi and
δ30Sidiatom data would be needed to provide more robust estimations and therefore
more rigorously test this, particularly when taking into consideration any progressive enrichment of the DSi pool as blooms persist.
The near-constant δ30Sidiatom composition
in open traps demonstrates the full preservation of the signal through
the water column and thereby justifies the use and application of the
technique in biogeochemical and palaeoenvironmental research. Data are
finally compared with lake sediment core samples, collected from the
south basin. Values of +1.30‰± 0.08 (2σ) and
+1.43‰± 0.13 (2σ) were derived for cores
BAIK13-1C (0.6–0.8 cm core depth) and at BAIK13-4F
(0.2–0.4 cm core depth) respectively. Trap data highlight the
absence of a fractionation factor associated with diatom dissolution
(ϵdissolution) (particularly as Synedra acus var radians, the
dominant taxa in the traps, is very susceptible to dissolution) down the water column and in the lake
surface sediments, thus validating the application of
δ30Sidiatom analyses in Lake Baikal and other
freshwater systems, in palaeoreconstructions.
Introduction
Records of diatom silicon isotopes
(δ30Sidiatom) provide a key means to
investigate changes in the global silicon cycle . Through measurements of
δ30Si (including diatoms
δ30Sidiatom and the dissolved silicon (DSi)
phase δ30SiDSi) it has been possible to
elucidate a more comprehensive understanding of biogeochemical
cycling both on continents e.g.
and in the ocean allowing, for example, an
assessment of the role of the marine biological pump in
regulating past changes in atmospheric pCO2(aq)e.g.. These studies and their
interpretations rely on work that has examined the mechanics of
diatom silicon isotope fractionation, demonstrating
an enrichment factor (ϵuptake: resulting from the
discrimination by diatoms against the heavier 30Si isotope) of
-1.1‰± 0.4 to -1.2‰± 0.2. In this case ϵuptake
is the per mil enrichment between the resulting product and its substrate. Estimations of
ϵuptake (-1.1‰± 0.4 to -1.2‰± 0.2) have to date shown it to be
independent of temperature, pCO2(aq) and other
vital effects , although more recent work on marine
diatoms in laboratory cultures has argued for a species-dependent fractionation effect .
In this case, ϵuptake estimations were documented between -0.53‰± 0.11
and -0.56‰± 0.07 for the Fragilariopsis kerguelensis species (depending on the culturing
strains used) and up to -2.09‰± 0.09 for the Chaetocerous brevis species .
A further assumption is that the isotopic signatures captured by
diatoms in the photic zone are faithfully transported through
the water column and into the sediment record, without
alteration from dissolution or other processes. This has been
questioned by evidence from diatom cultures which have revealed
a diatom dissolution induced fractionation
(ϵdissolution) of -0.55± 0.05 ‰
(from the preferential release of the heavier 30Si isotope into the
dissolved phase, over the lighter 28Si during dissolution) that is
independent of inter-species variations or temperature
(Demarest et al., 2009), although the importance and indeed
existence of an ϵdissolution has been
questioned by studies in the natural environment
and the laboratory . Whilst measurements of
δ30Sidiatom from sediment traps
, core-tops and in situ water column biogenic silica (BSi) in
marine systems have been used in isolation, an integrated record
is needed to document the fate of δ30Sidiatom
as diatoms sink through the water and become incorporated into
the sediment record, particularly in a lacustrine system where
hitherto no such work has taken place. Here, we present
pre-diatom bloom δ30SiDSiinitial and
δ30Sidiatom data from Lake Baikal, Siberia
(Fig. 1). By analysing samples from sediment traps through the
>1600m water column and a sediment core from the same
site (Fig. ), we document the good transfer of the
photic zone δ30SiDSi signature into diatoms
and into the sediment record.
Map of the Lake Baikal catchment, showing dominant inflowing rivers
and the Angara River outflow. The three catchments are identified as well as
the location of sites BAIK13-1 and BAIK13-4, where cores, sediment traps and
water column profiles were collected.
Unlike in ocean systems, where δ30Sidiatom analyses have been
used as a tracer for past surface water DSi utilisation and/or supply ,
its application in lake systems has not been as fully explored. To date, only a handful of studies have
aimed to validate the proxy in lacustrine systems via in situ measurements of seasonal DSi and BSi
. Here we present a further validation of the proxy (e.g. estimations of
ϵuptake), which also aims to address more fully the preservation of the signal to
the sediment record (ϵdissolution), which is of great importance in Lake Baikal where
dissolution of diatoms is prevalent. This is particularly important if measurements of δ30Sidiatom
are to be used to reconstruct past DSi utilisation and/or supply in relation to climatic and/or environmental
perturbations . Furthermore, with recent evidence highlighting the perturbation
of the steady-state delivery of DSi to ocean systems as a result of lacustrine burial (Frings et al., 2014),
the application of δ30Sidiatom techniques may be of great value in the future.
The main objectives of this study are to therefore
use annual sediment trap data as a means to document the good transfer of
surface δ30Sidiatom compositions to the sediment record and
validate the use of δ30Sidiatom methods in Lake Baikal as a
proxy for DSi utilisation/supply, and
use sediment trap data, for the first time, to attempt to validate fundamental
principles of ϵuptake and ϵdissolution, in Lake Baikal,
which to date have been more widely investigated in marine systems.
Lake Baikal
Lake Baikal
(103∘43′–109∘58′ E and
51∘28′–55∘47′ N) is the
world's deepest and most voluminous lake (23 615 km3)
containing one-fifth of global freshwater not stored in glaciers
and ice caps . Divided into three
basins (south, central and north), the Academician Ridge separates
the central (max depth 1642 m) and north (max depth
904 m) basins, while the Buguldeika ridge running
north-easterly from the shallow waters of the Selenga delta
divides the south (max depth 1460 m) and central basins
(Fig. ). This study will focus on
the southern basin (where sediment traps were deployed;
Fig. ), which has an estimated average depth of
853 m and a long water residence time
of 377–400 years, although the
residency time of silicon in the lake is estimated to be shorter
at 170 years.
Diatom dissolution in Lake Baikal occurs mainly at the bottom
sediment–water interface as opposed to during down-column settling
of diatoms , with showing that
remineralisation processes are an important constituent of surface
water nutrient renewal. Lake Baikal may be thought of as having
two differing water masses with the mesothermal maximum (MTM)
separating them at a depth of ca. 200–300 m. In the upper waters (above
ca. 200–300 m), both convective and wind forced mixing
occurs twice a year during spring
and autumn overturn periods. These overturn periods follow
(precede) ice-off (on) respectively and are separated by a period
of summer surface water stratification (e.g. above the
MTM). Diatom productivity in the lake is most notable during these
overturn periods although spring diatom blooms tend to dominate
annual productivity. Below ca. 300 m (e.g. below the MTM),
waters are permanently stratified (Ravens et al., 2000; Shimaraev
et al., 1994; Shimaraev and Granin, 1991), although despite this
the water column of Lake Baikal is oxygenated throughout, and it is
estimated that ca. 10 % of its deeper water is renewed each
year through downwelling episodes
.
MethodsSample locations
Upper water column (top 180 m) samples for DSi
concentrations and δ30SiDSi analyses were
collected on two occasions, when the lake was ice-covered, less
than 2 weeks apart, in March 2013 at site BAIK13-1 (sampling
a and b; Table ) in the south basin of Lake Baikal
(Fig. ; 51.76778∘ N and
104.41611∘ E) using a 2 L Van Dorn sampler. This
sampling coincided with the period when (1) riverine and
precipitation inflows to the lake are minimal, and (2)
photosynthetic activity in the lake was low (as demonstrated by
negligible in situ chlorophyll a measurements). We
argue that the average pre-bloom DSi and
δ30SiDSi values represent the baseline
nutrient conditions of the upper waters of the south
basin. Samples were filtered on collection through
0.4 µm polycarbonate filters (Whatman) before
storage in 125 mL acid-washed LDPE bottles, and acidified with
Superpure HCl to a pH above 2.
δ30SiDSi, respective uncertainties (2σ, unless otherwise stated) and
DSi concentrations
for sampling in South Basin of Lake Baikal at site BAIK13-1 in March 2013. Bold values correspond to the weighted average mean values (with respective errors) of data presented. Data are plotted in Fig. .
Depth (m)DSi (ppm)δ30SiDSi2σδ29SiDSi2σBAIK13-1a0.41.22+2.340.152+1.220.1023 Mar 2013101.19+2.170.152+1.180.092241.17+2.550.152+1.290.102401.12+2.180.11+1.180.061001.06+2.2210.31+1.2710.191800.66+2.400.08+1.230.04BAIK13-1b10.74+2.160.09+1.140.0412 Mar 2013101.21+2.440.152+1.200.052201.15+2.280.102+1.170.042501.16+2.290.162+1.260.112W.A MEAN+2.280.092+1.190.032MSDW4.11.9
1 This water sample was not pre-concentrated; refer to
methods. 2 These water sample values are weighted averages for sample
replicates that are analytically robust. These errors are at the 95 %
confidence interval.
At the same site, samples were collected from open sediment
traps (n=10) deployed by EAWAG and the Institute of Earth's
Crust/SB-RAS between March 2012 and March 2013 (from 100 to
1350 m water depth; Table ) and from monthly
sequencing traps (n=3) on the same array at a water depth of
100 m. For all open traps and for three of the monthly
traps (A4: 17 May to 7 June 2012, A6: 4 July to
31 July 2012 and A7: 31 July 2012 to 21 August 2012) it was
possible to extract sufficient diatoms for isotope analysis (see
below).
Open and sequencing trap (sampling interval 2012–2013)
δ30Sidiatom data and respective uncertainties (2σ,
unless otherwise stated). Mean values for open trap
δ30Sidiatom compositions are provided (in bold) along with
95 % confidence and the population MSWD value. Mean values for sequencing
trap δ30Sidiatom are also displayed in bold, with
respective 2 SD errors. Respective water column depths for open traps are
presented along with the relative abundance of S. acus var radians
(data not available for sequencing traps). All open trap data (Z2–Z11) are
plotted in Fig. .
1 These water sample values are weighted averages for sample
replicates that are analytically robust. These errors are at the 95 %
confidence interval.
Sediment cores were collected from site BAIK13-1
(51.76778∘ E and 104.41611∘ N; Fig. 1) and
from the nearby BAIK13-4 (51.69272∘ N and
104.30003∘ E; Fig. 1) using a UWITEC corer through
ca. 78–90 cm of ice with on-site sub-sampling at
0.25 cm intervals. Both sediment cores were dated using
210Pb dating (at University College London) using the
CRS (constant rate of supply) model , which is in
agreement with the individual 137Cs record for the two
cores. Sub-samples corresponding to 0.6–0.8 cm at
BAIK13-1 (core BAIK13-1C; age =2007AD± 2years) and 0.2–0.4 cm at BAIK13-4 (core
BAIK13-4F; age =2012AD± 7years: the
sampling period covered by the sediment traps) were processed to
obtain diatoms for δ30Sidiatom analysis.
Analytical methodsDiatom counting
To assess the taxonomic composition of diatoms in the open sediment
trap samples, diatom slides were prepared using a protocol that
omits any chemical treatments or centrifugation in order to
minimise further diatom dissolution and valve breakage (see
, for full details). Slides were counted using
a Zeiss light microscope with oil immersion and phase contrast
at ×1000 magnification. Microspheres at a known
concentration of 8.2×106 spheres mL-1 were added to all samples
in order to calculate diatom concentrations.
Silicon isotope sample preparation
Prior to isotope analysis, 0.7–1.0 g of sediment core (dry weight) and
trap material (wet weight) was digested of organic matter with analytical grade
H2O2 (30 %) at 75 ∘C for
ca. 12 h. This was followed by heavy density separation
using sodium polytungstate (Sometu Europa) at 2500 rpm for
15 min, with centrifuge break off, at a specific gravity
between 2.10 and 2.25 gmL-1 (adjusted to suit sample
contamination) to remove lithogenic particles and clays. Samples
were washed (up to 10 times) with deionised water at
2500 rpm for 5 min before visual inspection for
contaminants at ×-400 magnification on a Zeiss inverted
light microscope. All samples showed no evidence of external
contaminants that would impact the isotopic measurements (as displayed in light microscopy images; (Fig. ).
Silicon concentrations on all 25 samples (10 March lake water and
13 diatom opal trap samples (open Z and sequencing A traps) and 2 lake surface
sediment samples) were measured on an Inductively Coupled
Plasma-Mass Spectrometer (ICP-MS) (Agilent Technologies 7500) at
the British Geological Survey. Diatom samples were digested using
the NaOH fusion method with 1–3 mg of
powdered material fused with a 200 mgNaOH (Quartz
Merk) pellet in a silver crucible, covered within a Ni crucible
with lid, for 10 min in a muffle furnace at
730 ∘C. Following fusion, silver crucibles were placed in
a 30 mL Teflon Savillex beaker and rinsed with Milli Q
water before adding Ultra Purity Acid (UPA) HCl (Romil) to reach
a pH above 2. Samples were sonicated to ensure they were fully
dissolved and mixed before leaving them overnight in the dark.
Light microscopy images of open trap diatom species from Lake Baikal
(×1000). Images show the purity of samples used for
δ30Sidiatom analyses.
Water samples with DSi concentrations <1.5ppm were
pre-concentrated prior to column chemistry by evaporating
30 mL of sample to 5 mL at 70 ∘C on
a hotplate in a Teflon Savillex beaker in a laminar flow
hood. This follows , who showed no evaporative
alteration of silicon in samples and reference materials, provided
samples are not evaporated to dryness. This was not conducted for
sample BAIK1a-100 m as there was insufficient sample to do
so (Table ). Following pre-concentration, samples (and
reference and validation materials) were purified by passing
a known volume (between 1 and 2.5 mL depending on Si
concentration) through a 1.8 mL cationic resin bed (BioRad
AG50W-X12) and eluted with 3 mL of Milli Q
water in order to obtain an optimal Si concentration of between
3 and 10 ppm.
Silicon isotope analysis
All isotope analyses were carried out on a ThermoScientific
Neptune Plus MC-ICP-MS (multi collector inductively coupled
plasma mass spectrometer), operated in wet-plasma mode using the
method/settings outlined in . To overcome any
analytical bias due to differing matrices, samples and reference
materials were acidified using HCl (to a concentration of
0.05 M, using Romil UPA) and sulfuric acid (to
a concentration of 0.003 M, using Romil UPA) following
the recommendations of , the principle being that
doping samples and standards alike, above and beyond the natural
abundance of Cl- and SO42- will evoke
a similar mass bias response in each. All samples and reference
materials were doped with ∼300ppb magnesium (Mg,
Alfa Aesar SpectraPure) to allow the data to be corrected for the
effects of instrument-induced mass bias (Cardinal et al., 2003;
Hughes et al., 2011). In order to do this, Mg concentrations were
the same in both standard and samples.
Background signal contributions on 28Si were typically between 50
and 100 mV. Total procedural blanks for water samples were
15 ng compared to typical sample amounts of 4000 ng.
Procedural blank compositions are difficult to accurately measure (due to
exceedingly low Si signals), but as a worst-case scenario may have deviated
from sample compositions by ca. 0.38 ‰, contributing up to a
ca. 0.02 ‰ shift in typical sample compositions. This increases to
ca. 0.20 ‰ compositional shift in
exceptional cases, i.e. for one sample replicate (BAIK13-1 100 m), which has a Si
concentration of much less than 1 ppm. Fusion procedural blanks were ca. 42 ng
compared to typical fusion sample amounts of 4900 ng. Again, procedural blank compositions are
difficult to accurately measure, but may have deviated from sample compositions by ca. 0.04 ‰,
contributing up to a less than 0.01 ‰ shift in the sample compositions.
The validation material (diatomite) was analysed repeatedly during each
analytical session and a secondary reference material (an in-house river
water sample, RMR4) was also periodically analysed.
Data were corrected on-line for mass bias using an exponential function, assuming 24Mg/25Mg= 0.126633.
All uncertainties are reported at 2σ absolute, and incorporate an excess variance derived from the diatomite
validation material, which was quadratically added to the analytical uncertainty of each measurement.
δ30Si : δ29Si ratios of all data were compared with the mass-dependent
fractionation line (1.93), with which all data comply . Long-term (ca. 2 years)
variance for the method is the following: diatomite =+1.23‰± 0.16 (2σ, n=210)
(consensus value of +1.26‰± 0.2, 2σ;
) and RMR4 =+0.88‰± 0.20 (2σ, n=42).
Depicting water column sampling from Lake Baikal (180 m
below surface) of DSi concentrations (ppm) shown in green and
δ30SiDSi (‰) signatures in blue. The two sampling
intervals (BAIK13-1a and 1b) from March 2013 are both displayed. Note the
different sampling depths for these two data sets. All analytical errors of
uncertainty are shown in grey (2σ). All data correspond to
Table .
Results
Below-ice δ30SiDSi and DSi values in March 2013
from the top 1 m of the water column, collected within 2
weeks of each other, are +2.34‰± 0.15 (2σ),
1.22 ppm and +2.16‰± 0.09 (2σ),
0.74 ppm for BAIK13-1a and BAIK13-1b respectively (Fig. ;
Table ). DSi compositions show some variability with
depth at both sites, with overall trends showing decreasing
concentrations with depth (Fig. ), with the exception of
the surface sample at BAIK13-1b (0.74 ppm). As we are unable to fully
account for this variability in DSi concentrations, we use a weighted mean of surface water (e.g. above
the MTM) δ30SiDSi compositions, collected in
March before the diatom bloom period, to act as the baseline
isotopic composition (as will be discussed in Sect. 5.1). This is in order to compare with open trap data and
estimate the fractionation effect of diatoms
(ϵdissolution). In this case,
δ30SiDSi means are +2.28‰ (± 0.09,
95 % confidence; Table ), although some variability
is highlighted between data (e.g. mean square weighted deviation
(MSWD) = 4.1, n=10; Table ).
ICP-MS data of diatom opal show that ratios of Al:Si are all
<0.01 (data not shown), indicating that contamination in all
sediment trap and core samples is negligible. This was confirmed by
visual inspection of the diatom samples by light microscopy, prior
to analysis (Fig. ). Sediment trap diatoms are dominated (>85 %) by
the species Synedra acus var radians. Diatom
concentrations show some variability, varying between ca. 3×104 and 7×104valvesg-1 wet weight
(Fig. ), although lowest concentrations are seen in the
open sediment trap at 1350 m depth (3×104valvesg-1
wet weight Fig. ). This is
coincident with lowest diatom (S. acus var radians) valve
abundances also (86 %;
Table ). δ30Sidiatom data from the
open sediment traps show little variability (within analytical
uncertainty) down the water column profile in Lake Baikal
(Table ; Fig. ) with values ranging from
+1.11 to +1.38‰ (weighted mean
+1.23‰± 0.06 at 95 % confidence, MSWD = 2.9,
n=10). Sequencing (A) traps from May, July and August following
the onset of major diatom productivity in early spring show
a degree of variability with July and August
δ30Sidiatom data similar to the open sediment
traps but data from May lower at 0.67 ‰ ± 0.06
(Table ). Surface sediment results from BAIK13-1C
(0.6–0.8 cm core depth) and BAIK13-4F (0.2–0.4 cm
core depth) are very similar to both open (Z) and July–August
sequencing (A) traps with δ30Sidiatom signatures
of +1.30‰± 0.08 (2σ) and +1.43‰± 0.13 (2σ) respectively (Table ). Open trap total dry mass
fluxes show a near-constant value down the Lake Baikal water column (Table 2), with values ranging between 289.64 mgm-2d-1
at 1300 m water depth and 327.32 mgm-2d-1 at 900 m water depth.
Sequencing traps show the highest peak in total dry mass fluxes for the month of June
1649.52 mgm-2d-1 (although black particulate matter, of unknown origin, is
also present) and remain higher (compared to winter months) from July to October (Fig. ).
Open sediment trap (2012–2013) data from site BAIK13-1, south basin
Lake Baikal (brown symbols). Samples are displayed along a y axis of water
column depth. δ30Sidiatom data (‰) are expressed with
respective analytical errors (2σ) and surface sediment samples from
cores BAIK13-1C and BAIK13-4F are also displayed (green symbols) along with
the mean March surface (2013) water composition (blue symbol). Percentage
abundance of the dominant diatom Synedra acus var radians, diatom
concentrations (valves g-1 wet weight) and total dry mass sediment
fluxes (mgm-2d-1) are also provided. All data apart from
diatom concentrations are presented in Table .
Total dry mass sediment fluxes (mgm-2d-1) for
monthly sequencing traps, positioned at 100 m water depth in the
South Basin of Lake Baikal (2012–2013).
Discussion
The extreme continentality of the region around Lake Baikal
generates cold, dry winters that create an extensive ice cover
over the lake from October/November to May/June (north basin) and
from January to April/May (south basin) . This ice cover plays a key role
in regulating seasonal diatom productivity (as discussed in
Sect. 2) with blooms developing following the (1) reductions in
ice cover in spring and (2) after mixed-layer stratification in summer
. These
blooms are also coincident with periods of overturn in the upper
waters of the lake (e.g. above the MTM; Sect. 2). The March
δ30SiDSi data in this study were collected when
there was no/negligible chlorophyll a in the water column down
to a depth of 200 m. Accordingly, we interpret March
δ30SiDSi (+2.28‰± 0.09; 95 %
confidence interval, n=10; Table ) as reflecting the pre-spring bloom
isotopic composition of silicic acid in the mixed layer prior to
its uptake and fractionation in subsequent weeks as the spring
bloom develops. Whilst the open traps deployed from March
2012 to March 2013 may contain diatoms from both spring and autumnal
blooms, we suggest that δ30Sidiatom signatures
from these traps are primarily derived from the first bloom in spring/summer due
to the dominance of (1) spring diatom blooms in the annual record
, and (2) the dominance of spring/summer (May to August) blooming
S. acus var radians in the traps (>85 % relative
abundance (Fig. ). This is supported by total dry mass fluxes from the 100 m
sequencing traps which peak in June to September (Fig. ). We therefore argue that the open
trap data should be primarily reflective of spring to summer silicic acid utilisation
in the photic zone and so can be used to trace the fate of surface
water signatures through the water column and into the sediment
record.
Estimations of diatom fractionation factors (ϵ)
During biomineralisation, diatoms discriminate against the heavier
30Si isotope, preferentially incorporating
28Si into their frustules and leaving ambient waters
enriched in 30Si. Existing work from culture experiments
and marine environments has suggested an ϵ (the per mil enrichment factor between dissolved (DSi) and solid (diatom) phases) during
biomineralisation (ϵuptake) of -1.1± 0.4 to -1.2± 0.2 ‰
. Such estimations of ϵuptake
have been applied within both closed system and open system
modelling as a means of estimating variations in δ30Si compositions, although,
as discussed in Sect. 1, more recent evidence from cultured marine diatoms does point to a
species-dependent fractionation effect, which could range anywhere between -0.53‰± 0.11
(Fragilariaopsis kerguelensis species) and -2.09‰± 0.09 (Chaetocerous brevis species) .
Monthly data for both δ30SiDSi and
δ30Sidiatom are not
available in order to fully constrain ϵuptake over the course of the diatom
growing season in Lake Baikal (e.g. estimating variations between the open and closed system
models, where the import/export of DSi and BSi can be more fully estimated from surface waters).
Nevertheless, we can apply the data in this context to provide a snapshot of ϵuptake,
when a comparison is made between δ30SiDSiinitial and the first monthly sequencing
trap δ30Sidiatom compositions. We select the May δ30Sidiatom
signatures as we propose it reflects the initiation of the diatom bloom and therefore captures the
opal exported (based on total dry mass sediment flux data; Fig. ) from surface waters at
this time. These compositions will therefore most likely derive from DSi initial compositions (March
surface waters) before any (or minimal) progressive DSi enrichment occurs. We propose these data for
discursive reasons in order to extend the estimations of ϵuptake from lacustrine
systems and argue that they act as a snapshot estimation in this instance.
When examining sequencing trap total dry mass sediment fluxes for the year 2012–2013, numbers are
greatest for the month of June (Fig. ). This directly follows the period when δ30Sidiatom
isotopic compositions are the lowest of the three sequencing traps presented (May 2012 =+0.67‰± 0.06,2σ).
Although diatom concentrations are not available for the sequencing traps, we propose that these higher total dry mass
sediment fluxes (Fig. ) capture the exported May 2012 diatom bloom (e.g. the spring bloom) following ice-off
and, based on flux data, most likely represent the event more closely associated with pre-bloom surface water (e.g. March)
δ30SiDSi compositions (+2.28‰± 0.09; 95 % confidence interval, n=10; Table ).
Although later monthly δ30SiDSi data are not available, it is probable that the heavier isotopic
δ30Sidiatom compositions of July and August sequencing traps (Table ) reflect the
progressive enrichment of the DSi surface pool as the bloom develops. On the contrary, open trap data (Table )
constitute the mean annual δ30Sidiatom composition of diatoms, incorporating signatures derived from
throughout the year (a mean δ30Sidiatom composition of +1.23‰± 0.06; 95 % confidence
interval, n=10; Table ).
Although diatom uptake fractionation factors cannot be fully constrained in
this study (particularly when addressing open trap
δ30Sidiatom signatures), due to the absence of
comprehensive monthly DSi and BSi data, we can still provide an estimation of
ϵuptake for Lake Baikal. However, we emphasise that this is
for discussion purposes alone and that in order for this to be a more robust
estimation, there is a need for more seasonal investigations. Nevertheless,
if we argue that May δ30Sidiatom act as the dominant spring
bloom composition (+0.67‰± 0.06,2σ; Table )
exported from the surface zone and we compare this with our March 2013 mean
pre-bloom spring top water (incorporating 0 to 180 m)
δ30SiDSi composition (e.g. a DSi initial) of
+2.28‰ (± 0.09, 95 % confidence interval, n=10)
(Table ), we can derive an estimation of
ϵuptake of -1.61 ‰ (ranging between -1.46 and
-1.70 ‰ when taking account of respective analytical
uncertainty). We propose that this reflects more fully the initial uptake of DSi by diatoms, following ice-off and turnover,
while later sequential trap data (of July and August; +1.22‰± 0.08 and +1.37‰± 0.07 respectively;
Table ) quite possibly reflect the progressive enrichment of the surface DSi pool which cannot be constrained here.
Although this ϵuptake estimation of -1.61 ‰ falls within (or just outside of, e.g. -1.2‰± 0.2
from ) analytical uncertainty of existing estimations of ϵuptake (e.g. from temperate/sub-polar marine diatoms, -1.1‰± 0.4;
), we propose that they highlight the need for further estimations
within the literature. This is particularly important within the context of freshwater Si palaeoreconstructions where there is
a paucity of laboratory culture experiments, as the handful of in situ measurements derived from lacustrine studies have
calculated ϵuptake values closer to -1.1 ‰ e.g.. What is more, these
estimations of ϵuptake are further compounded by the more recent evidence which has thrown into question the
role that species-dependent fractionation factors may take during diatom biomineralisation (e.g. Sutton et al, 2013), although
investigations of this in lacustrine environments are still to be conducted.
The fate of diatom utilisation and δ30Sidiatom in Lake Baikal
Asides from the discussions surrounding the biological uptake of DSi by diatoms and the seasonal relationship between DSi
compositions, the isotopic composition of trap data (Table ) from
down the water column (except for the May sequencing trap)
(Table ) highlights the fact that the isotopic signature
incorporated into diatoms in the photic zone during
biomineralisation is safely transferred through the water column
without alteration, either from dissolution
(ϵdissolution) or other processes. Indeed, δ30Sidiatom signatures through the open traps
show minimal variation (mean of +1.23‰± 0.06 at
95 % confidence and MSWD of 2.9, n=10; Table ).
The role of dissolution is particularly important for the species Synedra acus var radians (which dominates open trap
compositions for the year 2012–2013; Table ) as the literature has demonstrated the fragility of this valve, particularly
its sensitivity to water column and surface sediment interface dissolution . While this species is sensitive
to dissolution, have nevertheless documented an increased percentage presence in south basin Lake Baikal sediments
over the past ca. 60 years (to between 10 and 20 % relative abundance), thought to represent a biological
response to late 20th century warming in this region.
Although the
majority of dissolution in Lake Baikal occurs at the
surface–sediment interface, with only 1 % of phytoplanktonic diatoms becoming incorporated into the sediment record
, δ30Sidiatom in sediment core
surface samples (i.e. post burial) at BAIK13-1C
(0.6–0.8 cm core depth) and at BAIK13-4F
(0.2–0.4 cm core depth) of +1.30‰± 0.08
(2σ) and +1.43‰± 0.13 (2σ)
respectively (Fig. ), are also similar (within
uncertainty) to the sediment trap data of +1.23‰± 0.06 (95 % confidence). These data confirm that in
contrast to previous work there is no
ϵdissolution or at least no other alteration of
the δ30Sidiatom signature from diatoms sinking
through the water column and during burial in the sediment
record. This in agreement with previous studies on marine diatoms
and validates that δ30Sidiatom
can be used in lacustrine sediment cores to constrain
biogeochemical cycling (building on work by ).
Conclusions
The first δ30Sidiatom data from lacustrine
sediment traps are presented from Lake Baikal, Siberia, and their
use in interpreting the fate of δ30Sidiatom in
the sediment record is shown. Mean values for open traps
(+1.23‰± 0.06 at 95 % confidence and MSWD of
2.9, n=10) suggest no alteration to the signal through the water column. Sequencing traps (May, July and August)
do show variation in their δ30Sidiatom signatures, with May the lowest at +0.67‰
(± 0.06). With total dry mass sediment fluxes highest in
June 2012, we argue that May represents the initial diatom bloom export from surface waters. As such, we provide a
snapshot estimation of ϵuptake in Lake Baikal of -1.61‰, when comparing May δ30Sidiatom
compositions and mean surface water March
δ30SiDSi compositions (+2.28‰± 0.09 at 95 % confidence). Although monthly synchronous δ30SiDSi and δ30Sidiatom
are not available to fully constrain ϵuptake (nor indeed any seasonal progressive enrichment of DSi in surface waters)
in Lake Baikal surface waters, the data provide a snapshot into stable isotope processes in freshwater systems which to date have not been fully explored. The near-constant
δ30Sidiatom compositions in open traps
demonstrates the full preservation of the signal through the water
column and thereby justifies the use and application of the
technique in biogeochemical and palaeoenvironmental research. In
particular, data highlight the absence of a fractionation factor
associated with diatom dissolution (ϵdissolution)
down the water column, of particular importance as the diatom species Synedra acus var. radians is known to be sensitive to
dissolution with estimations of only up to 5 % making it to the sediment interface . This is further reinforced by lake surface
sediment data from south basin cores, which also demonstrate the
absence of ϵdissolution due to the similar
compositions (within uncertainty) of surface sediment
δ30Sidiatom when compared to open trap data.
Acknowledgements
This project was funded by National Environmental Research Council
(NERC) standard grants NE/J00829X/1, NE/J010227/1 and NE/J007765/1
with research undertaken within the Centre of Environmental
Geochemistry, a joint venture between the British Geological Survey
and the University of Nottingham. The authors would like to thank
Simon Chenery and Thomas Barlow (BGS) for ICP-MS analyses of
dissolved silicon concentrations, in addition to Stephen Noble
(NIGL) for his assistance and knowledge. Additional thanks go to
Suzanne McGowan and Sarah Roberts (University of Nottingham) for
their invaluable assistance in the field as well as the numerous
other international colleagues that participated in the Lake Baikal
March 2013 field season. The authors are indebted to the assistance
of Nikolay M. Budnev (Irkutsk State University), the captain and
crew of the Geolog research boat and Dmitry Gladkochub (IEC) in
facilitating and organising all Russian fieldwork. All
210Pb dating was conducted at the Environmental Change
Research Centre, University College London.
Edited by: A. Shemesh
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