Introduction
Several organic proxies, based on different lipids, have been developed for
estimating sea surface temperatures (SSTs) (Brassell et al., 1986; Schouten et
al., 2002; Rampen et al., 2012). One of the first organic temperature proxies
developed was the U37K′ index (Prahl and Wakeham, 1987), which
is based on the relative abundances of C37 di- and tri-unsaturated
long-chain ketones. Culture and core top studies demonstrated that haptophyte
algae adjust the degree of alkenone unsaturation in response to their growth
temperature, and the U37K′ index is strongly related to average annual mean SST (Prahl and Wakeham, 1987; Müller et al., 1998).
However, the U37K′ index may be affected by variations in
nutrient concentrations, light limitation, and diagenesis (e.g., Hoefs et al.,
1998; Gong and Hollander, 1999; Prahl et al., 2003; Rontani et al., 2013).
Another organic temperature proxy commonly used in the last decade is the
TEX86 (Schouten et al., 2002, 2013), based on a ratio of glycerol dialkyl
glycerol tetraethers (GDGTs) with a varying number of cyclopentane moieties
in the membrane lipids of marine Thaumarchaeota (Sinninghe Damsté et al.,
2002). The TEX86 is strongly correlated with satellite-derived annual
mean SST in global core top data sets (Kim et al., 2008, 2010; Ho et al., 2014). However, marine Thaumarchaeota
occur throughout the whole water column (e.g., Karner et al., 2001), and thus
the TEX86 often reflects the water temperature of subsurface water
masses (e.g., Huguet et al., 2007). The TEX86-SST calibrations by Kim et
al. (2010) distinguish between low-temperature (< 15 ∘C,
TEX86L) and high-temperature (> 15 ∘C,
TEX86H) regions, which takes into account an increased relative
abundance of the crenarchaeol regioisomer in subtropical regions.
Furthermore, a subsequent recalibration of TEX86L with
depth-integrated annual mean temperatures from 0 to 200 m water depth was
established following evidence of abundant subsurface Thaumarchaeota in
Antarctic regions (Kim et al., 2012b). The TEX86 seems to be less
affected by diagenesis than the U37K′ index (Schouten et al.,
2004; Kim et al., 2009b), but it can be biased by contributions of
soil-derived isoprenoid GDGTs in coastal marine sediments, which can be
assessed by the BIT (Branched and Isoprenoid Tetraether) index (Hopmans et
al., 2004). A terrestrial effect on TEX86 may be substantial when BIT
values are > 0.3 (Weijers et al., 2006, 2009), although it has been noted
that this threshold depends on the location (cf. Schouten et al., 2013). More
clues may be obtained by correlating the BIT index with TEX86 values,
where a significant correlation could indicate the impact of terrestrial
input.
Recently, Rampen et al. (2012) proposed the long-chain diol index (LDI),
based on the fractional abundances of C30 1,15-alkyl diol relative to
those of C28 1,13-, C30 1,13- and C30 1,15-alkyl diols
(hereafter referred to as diols), showing a strong correlation with annual mean
SST in globally distributed surface sediments. The LDI proxy seems to be
independent of salinity but the effect of degradation or nutrient limitation
is not yet known. C28 and C30 1,13-diols and C30 and C32
1,15-diols have been reported in eustigmatophyte algae (Volkman et al., 1992,
1999; Gelin et al., 1997; Méjanelle et al., 2003), but since these algae
are not widely reported from open-ocean settings and the diol distributions
in cultured eustigmatophytes differ from those found in the natural
environment, there are still uncertainties about the biological source of
long-chain 1,13- and 1,15-diols in marine sediments (Versteegh et al., 1997,
2000; Rampen et al., 2012). Besides 1,13- and 1,15-diols, 1,14-diols have
also been identified in marine sediments. These lipids have been reported in
Proboscia diatoms, which are thought to be their source (Sinninghe
Damsté et al., 2003; Rampen et al., 2007), although they have also been
identified in the marine alga Apedinella radians (Rampen et al.,
2011).
SST reconstructions derived from the various organic molecular proxies can
differ as proxies may reflect temperatures of different seasons or different
habitat depths, and proxies may also be affected by environmental factors
other than temperature. Importantly, the use of organic proxies in high-latitude regions is often problematic. Previous studies have raised doubts
about the applicability of alkenone paleothermometry at high latitudes, due
to the nonlinearity of the relationship of U37K′ index with
SST at low temperatures (< 6 ∘C) and the high, erratic abundance
of the C37:4 alkenone (e.g., Sikes and Volkman, 1993; Rosell-Melé et
al., 1994; Rosell-Melé, 1998; Rosell-Melé and Comes, 1999; Conte et
al., 2006). Concerning the TEX86, studies in subpolar regions have
observed significant deviations in reconstructed SST, even with the
TEX86L calibration (Ho et al., 2014, and references therein),
as well as a substantial scatter in the correlation (Kim et al., 2010). The
LDI has been applied thus far in the midlatitudes of the Northern (Rampen et
al., 2012; Lopes dos Santos et al., 2013; Rodrigo-Gámiz et al., 2014) and
Southern Hemispheres (Smith et al., 2013) but not in high-latitude regions,
although surface sediments from high latitudes were included in the surface
sediment calibration (cf. Rampen et al., 2012).
To test and constrain the application of the different organic temperature
proxies at high latitudes, we have collected suspended particulate matter,
sedimenting particles, and marine surface sediments from several stations
distributed around Iceland. This region is of particular interest for
climate studies because it is in the transition zone between polar and
temperate climate regimes and is thereby subjected to large variations in
hydrographic conditions (Ólafsson, 1999). Thus, this high-latitude
region presents an ideal setting for testing and applying organic
temperature proxies, including the novel LDI, in cold regions.
Material and methods
Oceanographic setting
The oceanographic configuration around Iceland is predominantly characterized
by the interplay of two water masses, i.e., warm and saltier Atlantic water
versus cold Arctic or subpolar waters. From the south flows the Irminger
Current (IC) – a branch of the warm and salty Atlantic current, which moves
northwards along the west Iceland coast and continues along the north Iceland
coast, extending down to several hundred meters (Hopkins, 1991) (Fig. 1).
Flowing southward from north to west Iceland, the East Greenland Current
(EGC) transports cold and low-salinity polar waters. A branch of the EGC, the
East Iceland Current (EIC), turns eastward and flows southward along the east
coast of Iceland (Hopkins, 1991). The EGC carries icebergs and sea ice formed
in the Arctic Ocean and in East Greenland fjords (Sigtryggsson, 1972). The
wide transitional zone between the polar waters and the Atlantic waters in
the Denmark Strait is defined as the polar front. The position of this front
is known to vary on annual, interannual and longer timescales (Malmberg and
Jónsson 1997; Sigtryggsson, 1972). During episodes of extensive sea ice,
the contribution of polar waters from the EGC to EIC is relatively large and
responsible for carrying sea ice, icebergs and cold, low-salinity waters to
the northwest coast of Iceland (Sigtryggsson, 1972).
Bathymetric map of the study area with the location of the
different sampling stations around Iceland. Filled circles indicate surface
sediment stations with color coding according to the area of location, i.e.,
yellow and green for the northern stations, red for the shallow stations in
the south of Iceland and blue for the deep southern stations. Black and blue
inverse triangles with filled circles indicate surface particulate matter
stations around Iceland sampled during July 2011 and the transect from Iceland
Basin (St A) to Reykjavik (St G) sampled during July 2012, respectively. The
red star indicates the location of sediment trap deployment. Dashed blue
arrows show the theoretical circulation of the different water masses.
The polar front is also expressed in the phytoplankton blooms around
Iceland. In the Arctic or subpolar waters, the early onset of stratification
in spring gives rise to a rapid shallowing of the mixed layer and triggers
the early spring bloom (in early April) north of Iceland. In the south of
Iceland, the weakly stratified water column in the Atlantic water and an
associated deep mixed layer delays the spring bloom (e.g., Zhai et al., 2012,
and references therein). The spring bloom initiation varies by up to a month
between different regions around Iceland. Within the southern Iceland shelf
region, the spring bloom generally starts in near-shore waters (mid-May) and
is delayed with increasing distance from the coast, where it is affected by
the interaction between runoff and wind regime (Thordardottir, 1986).
Sample collection
Sample material was collected around Iceland during long-chain diol cruises
(Cruise Report 64PE341, de Haas, 2011; and Cruise Report 64PE357, Baas and
Koning, 2012) in the summer of 2011 and 2012 on board the R/V Pelagia
(Fig. 1, Table 1). During July 2011, suspended particulate matter (SPM) from
a water depth of ca. 5 m and surface sediments were collected at different
stations (St) around Iceland (Table 1), and a sediment trap was deployed at
1850 m water depth at St 1 (water depth at this station is 2255 m), located
in the northern part of the Iceland Basin, to recover sinking particulate
matter (Fig. 1). During July 2012, SPM was collected at 20 and 50 m water
depth in a transect from the site of the sediment trap deployment to
Reykjavik (Fig. 1, Table 1) after the sediment trap was recovered.
Location, depth and other information on each material collected at
different stations around Iceland.
Station
Latitude
Longitude
Depth
Core
Volume
length
pumped
(m.b.s.l.)
(cm)
(L)
Sediment trap
1
N 61∘59.757′
W 16∘00.191′
1850
SPM collected around Iceland July 2011
1
N 62∘0.008′
W 16∘0.016′
5
no data
7
N 61∘29.917′
W 24∘10.333′
5
26
8
N 64∘17.583′
W 24∘8.811′
5
25
10
N 66∘40.647′
W 24∘10.794′
5
130
13
N 67∘30.098′
W 15∘4.109′
5
164
16
N 63∘59.132′
W 12∘12.472′
6
10
SPM collected along transect July 2012
A
N 61∘59.757′
W 16∘00.191′
20
36
A
N 61∘59.757′
W 16∘00.191′
50
229
B
N 62∘14.963′
W 16∘51.877′
50
199
C
N 62∘29.635′
W 17∘50.287′
50
183
D
N 62∘44.568′
W 18∘48.771′
50
216
E
N 62∘58.981′
W 19∘47.270′
50
220
F
N 63∘12.696′
W 20∘44.820′
50
219
G
N 63∘27.319′
W 21∘44.951′
50
219
Sediment cores
1
N 62∘0.019′
W 15∘59.951′
2255
18
3
N 63∘21.972′
W 16∘37.696′
240
5
5
N 63∘34.996′
W 22∘8.624′
188
15
6
N 63∘14.294′
W 22∘33.685′
315
15
7
N 61∘29.913′
W 24∘10.335′
1628
28
8
N 64∘17.591′
W 24∘8.825′
260
33
10
N 66∘40.647′
W 24∘10.770′
241
30
11
N 66∘37.999′
W 20∘50.006′
367
10
13
N 67∘30.098′
W 15∘4.153′
884
10
14
N 66∘18.186′
W 13∘58.369′
262
no data
SPM was obtained by filtering through 142 mm diameter glass-fiber filters
(GFFs) with a pore diameter of 0.7 µm using a McLane Research
Laboratories WTS 6-1-142LV in situ pump installed on a CTD (conductivity–temperature–depth) rosette frame. The
CTD measured the vertical distribution of temperature, salinity, turbidity,
oxygen and fluorescence. SPM filters were frozen directly after filtration
and stored at -20 ∘C until analysis.
A McLane Parflux 78H-21 sediment trap (aperture area: 0.5 m2) was set
to collect sinking material every 17.5 days in a 21-cup automated sampling
carousel covering one complete annual cycle (Table 2). Prior to mooring the
sediment trap, the sample cups were filled with a mercuric-chloride-poisoned
and borax-buffered solution of seawater collected from the deployment depth
(1 g L-1 of HgCl2; pH ∼ 8.5). After recovery of the
sediment trap, collecting cups were stored in the dark at 4 ∘C.
Sampling intervals in the sediment trap and fluxes of lipids. For
proxy values and derived temperatures, see Table S2.
Period
Start
Sampling
Bulk
C37:2+ C37:3
GDGT-0
TEX86-GDGTs1
Crenarchaeol
Sat. 1,14-diols
Unsat. 1,14-diols
LDI-diol2
(mm/dd/yy)
interval
flux
flux
flux
flux
flux
flux
flux
flux
(mg m-2
(µg m-2
(µg m-2
(µg m-2
(µg m-2
(ng m-2
(ng m-2
(ng m-2
(days)
day-1)
day-1)
day-1)
day-1)
day-1)
day-1)
day-1)
day-1)
1
07/15/11
16.5
166
115
2800
640
2600
500
280
160
2
08/01/11
17.5
9.3
0.91
220
53
174
32
n.d.
10.7
3
08/19/11
17.5
21
0.32
280
55
240
13.6
2.8
4.8
4
09/05/11
17.5
75
1.03
3000
550
2900
550
3700
120
5
09/23/11
17.5
188
n.d.
2600
610
2600
770
1620
147
6
10/10/11
17.5
49
1.04
1960
380
1800
450
530
96
7
10/27/11
17.5
7.5
0.10
370
94
330
23
2.0
6.3
8
11/14/11
17.5
28
0.11
440
132
390
33
52
7.4
9
12/01/11
17.5
28
0.32
1170
380
1130
86
154
29
10
12/19/11
17.5
16.8
0.27
600
220
590
31
49
11.0
11
01/05/12
17.5
16.6
0.18
720
270
720
57
85
16.2
12
01/23/12
17.5
11.2
0.20
760
300
740
46
n.d.
12.0
13
02/09/12
17.5
11.2
0.21
900
340
890
41
59
19.2
14
02/26/12
17.5
9.3
0.12
410
159
390
33
45
9.0
15
03/15/12
17.5
18.3
0.02
280
83
198
41
20
3.5
16
04/01/12
17.5
7.5
0.08
390
156
370
6.8
3.4
2.3
17
04/19/12
17.5
3.7
0.04
173
64
163
3.8
5.1
1.50
18
05/06/12
17.5
108
54
4900
690
4000
540
420
165
19
05/24/12
17.5
160
134
14 400
2300
11 000
410
470
155
20
06/10/12
17.5
134
74
10 900
1970
9700
185
260
106
21
06/27/12
17.5
45
2.6
1870
380
1550
33
32
9.8
n.d.: not detected;
1 GDGTs with one, two and three cyclopentane moieties and the
crenarchaeol regioisomer;
2 C28 and C30 1,13- and C30 1,15-diol.
Sediment cores were taken using a multicorer, sliced into 1 cm wide sections and
frozen onboard. The upper 1 cm was analyzed for biomarkers.
Extraction and lipid fractionation
In the laboratory, any larger “swimmers” were removed from the sediment
trap collecting cups prior to subdividing into two volumetrically split
aliquots using a Folsom wet splitter (Sell and Evans, 1982) with a precision
of > 95 %. One half was stored in the dark at 4 ∘C, and the
second half was used for lipid analysis. The trap material was centrifuged at
3000 rpm for 15 min, followed by pipetting the water layer and washing with
bidistilled H2O (3×) to remove the HgCl2 and borax solution. The
sediment trap samples (n=21) and surface sediment samples (n=10) were
freeze-dried, homogenized in agate mortar and extracted after the addition of
extracted diatomaceous earth in an accelerated solvent extractor 350 (ASE
350, DIONEX) using a solvent mixture of 9:1 (v:v) dichloromethane (DCM)
to methanol (MeOH) at 100 ∘C and 7.6 × 106 Pa. The
solvent from all the extracts was reduced by TurboVap LV Caliper, dried over
Na2SO4 and concentrated under a stream of N2, yielding a total
lipid extract (TLE). Three internal standards
were added to the TLE from the sediment trap samples, i.e., 10-nonadecanone (C19 ketone) for alkenones,
C22 7,16-diol for long-chain diols and the C46 glycerol trialkyl
glycerol tetraether (GTGT) for GDGTs (Huguet et al., 2006). Activated copper
and DCM were added to the TLEs of the sediment trap samples that were found
to contain elemental sulfur. After being stirring overnight with a small stirring
bar, the TLEs were filtered over a pipette column containing Na2SO4
and dried under a stream of N2.
SPM filters (n=14) were freeze-dried and half of each filter was
saponified according to de Leeuw et al. (1983) by refluxing for 1 h with
1 M KOH in MeOH (96 %). After cooling, the solvent was acidified with 2 N HCl in MeOH (1:1, v:v) to a pH of 2, and transferred to a separatory funnel
containing bidistilled H2O. The residual filters were further extracted
using H2O : MeOH (1:1, v:v, ×1), MeOH (×1) and DCM
(×3), and all solvents were combined in the separatory funnel. The
DCM layer in the separatory funnel was separated from the H2O : MeOH layer
and the remaining H2O : MeOH layer was extracted three times with DCM.
DCM layers were combined and rotary evaporated to near dryness. Thereafter,
the obtained extracts were acid hydrolyzed (3 h reflux with 2 N
HCl : MeOH, 1:1, v:v) and neutralized with 1 M KOH in MeOH (96 %).
Then 3 mL bidistilled H2O was added to the acid hydrolyzed extracts and the
lipids were extracted using DCM (4×). The filter material remaining
after base hydrolysis was also acid hydrolyzed (3 h reflux with 2 N
HCl : MeOH, 1:1, v:v). After cooling, the solvent was neutralized with
1 M KOH in MeOH (96 %) and transferred to a separatory funnel containing
bidistilled H2O. Subsequently, the acid-hydrolyzed residual filters were
extracted using H2O : MeOH (1:1, v:v, ×1), MeOH (×1)
and DCM (×3), and the extracts were combined in the separatory funnel.
The DCM layer was collected and the remaining H2O : MeOH layer was
extracted three times with DCM. All extracts, obtained by saponification and
acid hydrolysis, were combined, dried under N2, eluted in DCM over a
pipette column containing Na2SO4 and dried under a stream of
N2.
Extracts of SPM, descending particles and surface sediments were separated
into apolar, ketone (containing alkenones) and polar fractions (containing
GDGTs and long-chain diols) by column chromatography using a Pasteur pipette
filled with Al2O3 (activated for 2 h at 150 ∘C) using
9:1 (v:v) hexane : DCM, 1:1 (v:v) hexane : DCM, and 1:1 (v:v)
DCM : MeOH as the eluents, respectively.
Alkenone analysis
The ketone fractions were dried under N2 and redissolved in an
appropriate volume (20–100 µL) of hexane. Analysis of the di-
(C37:2) and tri-unsaturated (C37:3) alkenones was performed on an
Hewlett Packard 6890 gas chromatograph (GC) using a 50 m CP Sil-5 column
(0.32 mm diameter, film thickness of 0.12 µm), equipped with a flame
ionization detector and helium as the carrier gas. The temperature of the
oven was initially 70 ∘C and increased, with a rate of 20 ∘C
per minute to 200 ∘C and subsequently with a rate of 3 ∘C per minute to 320 ∘C, at which it was held for 25 min. Alkenone relative
abundances were determined by the integration of relevant peak areas.
The U37K′ index (Eq. 1) was used to estimate SSTs according to
the equation by Prahl and Wakeham (1987):
U37K′=[C37:2]/([C37:2]+[C37:3]).
U37K′ values were converted to SSTs using the global core top
calibration of Müller et al. (1998):
U37K′=0.033×SST+0.044.
The calibration error associated with the U37K′ is
1.5 ∘C (Müller et al., 1998). Five samples were run in
duplicate,
resulting in a standard deviation (SD) of 0.02 or better, equivalent to
0.8 ∘C.
GDGT analysis
Polar fractions of the extracts, containing the GDGTs, were dried under a
stream of N2, redissolved by sonication (5 min) in 200 µL
hexane : propanol (99:1, v:v), and filtered through 0.45 µm
polytetrafluoroethylene (PTFE) filters. GDGTs were analyzed by
high-performance liquid chromatography–mass spectrometry (HPLC/MS) following
the method described by Schouten et al. (2007). Samples were analyzed on an
Agilent 1100 series LC/MSD SL. A Prevail Cyano column
(150 mm × 2.1 mm, 3 mm) was used with hexane : isopropanol
(99:1, v:v) as an eluent. After the first 5 min, the eluent increased by
a linear gradient up to 1.8 % isopropanol (vol) over the next 45 min at
a flow rate of 0.2 mL min-1. Scanning was performed in single-ion
monitoring (SIM) mode. The identification and quantification of the GDGT isomers
and C46 GTGT standard was achieved by integrating the peak areas of
relevant peaks in m/z 1302, 1300, 1298, 1296, 1292, 1050, 1036, 1022 and
744 mass chromatograms.
The TEX86 and TEX86L index were calculated following Kim
et al. (2010):
TEX86=([GDGT2]+[GDGT3]+[cren′]/([GDGT1]+[GDGT2]+[GDGT3]+[cren′])TEX86L=([GDGT2]/([GDGT 1]+[GDGT2]+[GDGT3]),
where numbers correspond to isoprenoid GDGTs from marine
Thaumarchaeota with 1, 2 or 3 cyclopentane moieties, and cren′ corresponds to
crenarchaeol regioisomer, which has the antiparallel configuration to
crenarchaeol (Sinninghe Damsté et al., 2002).
TEX86 and TEX86L values were converted to SSTs using
calibrations (Eqs. 5, 6) proposed by Kim et al. (2010):
SST=81.5×TEX86-26.6SST=67.5×log(TEX86L)+46.9.
Calibration errors are 5.2 and 4 ∘C, due to the large
scatter in the polar regions (Kim et al., 2010).
Furthermore, the Kim et al. (2012b) TEX86L temperature
calibration with 0–200 m water depth was also used:
T(0-200m)=50.8×log(TEX86L)+36.1.
The BIT index, a measure for soil versus
marine organic matter input in marine sediments, was calculated according to
Hopmans et al. (2004):
BIT=([GDGT-I]+[GDGT-II]+[GDGT-III])/([crenarchaeol]+[GDGT-I]+[GDGT-II]+[GDGT-III]),
where roman numerals correspond to the major branched GDGTs (see Hopmans et
al., 2004).
A total of 17 samples were run in duplicate for TEX86 and the BIT,
showing an SD of 0.09, equivalent to 1.0 ∘C or better for
TEX86L, and an SD of 0.002 or better for the BIT index.
Long-chain diol analysis
After GDGT analysis, polar fractions were silylated by the addition of 15 µL
N,O-bis(trimethylsilyl)trifluoroacetamide (BSTFA) and pyridine and heating in
an oven at 60 ∘C for 20 min. Long-chain diol distributions were
analyzed using a Thermo trace gas chromatograph (GC) Ultra coupled to Thermo
DSQ MS. A 25 m CP Sil-5 fused silica capillary column was
used (25 m × 0.32 mm; film thickness = 0.12 µm) with helium as
the carrier gas. The column was directly inserted into the electron impact
ion source of the DSQ quadrupole MS with an ionization energy of 70 eV.
Samples were dissolved in 50–100 µL ethyl acetate and injected at
70 ∘C. The oven was programmed to increase first at a rate of
20 ∘C per minute to 130 ∘C and then at a rate of
4 ∘C per minute to the final temperature of 320 ∘C (held for 25
min). Various long-chain diols and the C22 7,16-diol standard were
quantified using an SIM of m/z 299, 313, 327, 341, and 187, respectively (cf.
Rampen et al., 2012). The selected ions contributed on average 6.5 % to
the total ion counts for unsaturated long-chain diols, 9.7 % to the total
ion counts for the saturated long-chain diols, and 19 % to the total ion
counts for the C22 7,16-diol standard.
The Long-chain Diol Index (LDI) was calculated and converted to SST
following Rampen et al. (2012):
LDI=[C301,15-diol]/([C281,13-diol]+[C301,13-diol]+[C301,15-diol])LDI=0.033×SST+0.095
The calibration error for the LDI is 2.0 ∘C (Rampen et al., 2012).
Replicate analysis of three samples showed a mean SD of 0.023, equivalent to
0.7 ∘C.
Results
Suspended particulate matter
SPM was collected during two cruises: in July 2011 at six stations around
Iceland at ca. 5 m water depth, and in July 2012 in a transect (St A–G)
from the northern Iceland Basin to Reykjavik at 50 m and, at some
locations, also at 20 m water depth (Fig. 1).
Alkenones were detected in all samples except from St 13. Values for the
U37K′ index varied between 0.26 and 0.53 (or 6.4 and 14.7 ∘C when translated into temperature) in the SPM around Iceland
during summer 2011 (Fig. 2a, open green diamonds) and between 0.26 and 0.45
(corresponding to 6.5 to 12.5 ∘C) during summer 2012 (Fig. 2b, open
green diamonds). GDGTs were detected in all samples and the TEX86 values
ranged between 0.49 and 0.55 (corresponding to 13.1 to 17.9 ∘C) in
SPM around Iceland (Fig. 2a, dark blue circles) and between 0.34 and 0.50
(corresponding to 1.0 to 14.4 ∘C) along the transect of 2012
(Fig. 2b, dark blue circles). TEX86L varied between 0.28 and
0.32 (corresponding to 9.4 to 13.7 ∘C) around Iceland (Fig. 2a, open
blue circles) and between 0.22 and 0.29 (corresponding to 2.5 to
10.6 ∘C) along the transect (Fig. 2b, open blue circles). Long-chain
alkyl diols were not detected in SPM around Iceland collected during summer
2011 (Fig. 2a), while C28 and C30 1,13- and 1,14-diols and
C30 and C32 1,15-diols were only detected in SPM collected at St A,
B, F and G during the transect in the summer of 2012. LDI values varied
between 0.08 and 0.49, corresponding to -0.4 to 12 ∘C when
converted into temperature (Fig. 2b, open brown squares). Values for
U37K′, TEX86 and LDI and corresponding temperatures are
reported in Supplement Table S1.
U37K′-, TEX86L- and LDI-derived
temperatures from SPM obtained at the different sampling stations around
Iceland. Panel (a): SPM collected at ca. 5 m water depth during July 2011; panel (b): SPM
collected at 50 m water depth collected during July 2012. Open green
diamonds indicate U37K′-derived temperatures; filled dark blue
circles indicate TEX86-derived temperatures using calibration by Kim et
al. (2010a); open blue circles indicate TEX86L-derived
temperatures using calibration by Kim et al. (2010a); open brown squares
indicate LDI-derived temperatures. Orange symbols indicate in situ SST
measured with the CTD; pink symbols indicate satellite SST from NOAA remote-sensing records at the time of sample collection, i.e., July 2011 and July 2012, and purple symbols indicate summer mean temperatures at
50 m water depth from the WOA09 (World Ocean Atlas) database.
Descending particulate matter
Sinking particulate matter was collected between 15 July 2011 and
16 July 2012 at St 1, using a sediment trap deployed at 1850 m water depth.
Bulk sediment fluxes varied between 4 and 165 mg m-2 day-1
(Fig. 3b), with high fluxes occurring in July, September and October 2011 and from May to July 2012. C37 alkenone fluxes varied between 0.02 and
130 µg m-2 day-1, peaking during spring and summer,
i.e., in July 2011 and in May and June 2012 (Table 2; Fig. 3c). Fluxes of the
GDGTs used for the calculation of the TEX86 index ranged between 53 and
2300 µg m-2 day-1 with highest values recorded from May
to June 2012 (Table 2; Fig. 3d). GDGT-0 and crenarchaeol fluxes followed the
same pattern as those of the GDGTs used in the TEX86, ranging from
minimum values of ca. 170 µg m-2 day-1 to a maximum of 15
and 11 mg m-2 day-1, respectively (Fig. 3d). Values for the BIT
index were always below < 0.01. Fluxes of long-chain 1,13- and 1,15-diols
used in the LDI were low compared to alkenones and GDGT fluxes and varied
between 1.5 and 170 ng m-2 day-1, with highest values recorded
during July, September and October 2011 and from May to June 2012 (Table 2;
Fig. 3e). Generally, the flux of the C30 1,15-diol was always low (up to
2 ng m-2 day-1) or even below the detection limit for most of the
intervals. The fluxes of saturated and monounsaturated C28 and C30
1,14-diols were substantially higher than those of the 1,13- and 1,15-diols
(Fig. 3e). The highest summed mass flux of the C28 and C30
monounsaturated 1,14-diols was recorded in September 2011 with a flux of
3.7 µg m-2 day-1 (Fig. 3e). C28 and C30
saturated 1,14-diol fluxes varied between minimum values of
3.8 ng m-2 day-1 during the second half of April and maximum values of
770 ng m-2 day-1, with high fluxes recorded during July,
September and October 2011 and May and June 2012 (Table 2; Fig. 3e).
Panel (a): variations in the net primary productivity from July 2011 to
July 2012 derived from OceanColor Web (Behrenfeld and Falkowski, 1997). Bar
plots of fluxes of (b) particulate matter, (c) C37 alkenones, (d)
isoprenoid GDGTs, and (e) long-chain diols as determined from sediment trap
data. Numbers refer to sampling intervals specified in Table 2.
U37K′-based temperatures derived from settling particles
ranged from 5.3 to 11.4 ∘C (Fig. 4), with maximum values recorded at
the end of summer (September 2011) and late winter (end of February 2012)
and minimum values in spring (from May to June 2012) (Fig. 4, green line),
when the highest flux is observed. Temperature estimates based on TEX86
varied between 6.8 and 9.6 ∘C (Fig. 4, dark blue line) and those
based on TEX86L varied between 12.6 and 17.5 ∘C
(Fig. 4, light blue line), with the highest values recorded from November 2011
to April 2012. TEX86L-temperature estimates based on the
0–200 m calibration showed absolute values ranging from 10.3 to
13.9 ∘C (Fig. 4, red line). For sampling periods when 1,13- and
1,15-diols were detected, the LDI-based temperatures vary between -2.7 and
0.2 ∘C (Fig. 4, brown line and open squares). Values for
U37K′, TEX86 and LDI and corresponding temperatures are
reported in Table S2.
Changes in temperatures derived from U37K′ (green line and diamonds),
TEX86 (dark blue line and open circles), TEX86L (light
blue line and open circles), TEX86L 0–200 m (light
red line and open circles), and LDI (brown line and open squares) in descending particles over one complete annual cycle, from
July 2011 to July 2012. Numbers refer to sampling intervals specified in
Table 2, and data points represent the center of collection intervals.
Satellite temperatures (from AVHRR, NOAA) at St 1 during the sampling period
are indicated with a dashed orange line and 0–200 mean temperatures from
WOA09 are indicated with a dashed purple line.
Surface sediments
Surface sediments were collected in July 2011 from 10 stations around Iceland
(Fig. 1; Table 1). The U37K′ index varied between 0.26 and
0.53 in the surface sediments, yielding SST estimates between 7 and
11 ∘C for St 13 and St 7, respectively (Fig. 5, open green
diamonds). TEX86 ranged between 0.36 and 0.44 with SST estimates between
2.4 and 9.2 ∘C (Fig. 5, dark blue circles). TEX86L
ranged between 0.19 and 0.33, resulting in TEX86L-derived temperatures between -1.2 ∘C at St 13 and 14 ∘C
at S. 1 (Fig. 5, open light blue circles) or between -0.1 and
11.4 ∘C using the 0–200 m calibration (Fig. 5, open red circles).
LDI values varied between 0.02 and 0.27, with SST estimates between -2.1
and 5.2 ∘C, reaching high values in the coastal stations, St 3 and
St 8 (Fig. 5, open brown squares). Values for U37K′,
TEX86 and LDI and corresponding temperatures are reported in Table S3.
Temperatures in surface sediments from stations around
Iceland from U37K′ (open green diamonds), TEX86 (dark
blue circles), TEX86L (open light blue circles),
TEX86L 0–200 m (open red circles) and LDI (open brown
squares) derived . Annual mean SSTs at each station obtained from the WOA09 database
are indicated as purple crosses.
Discussion
U37K′
Long-chain alkenones are produced by several haptophyte algal species
thriving in the photic zone (Volkman et al., 1980, 1995; Marlowe et al.,
1984) and are, therefore, thought to reflect SST. Although previous studies
of cold polar waters (< 4 ∘C) of the North Atlantic have shown
relatively high abundances of C37:4 (e.g., Sicre et al., 2002), the
C37 alkenones in SPM, descending particles and surface sediments around
Iceland comprised only C37:3 and C37:2, and no C37:4 was
detected. Comparison of U37K′-derived temperatures with
in situ temperatures showed generally lower U37K′-derived
temperatures, differing by up to 3.4 ∘C for SPM around Iceland
(Fig. 2a) and by up to 6.6 ∘C for the SPM transect (Fig. 2b). Reduced
temperature differences (up to 2.6 ∘C) were observed when we
compared U37K′-derived SSTs with summer temperatures at 50 m
water depth (Fig. 2b, purple crosses; derived from the World Ocean Atlas
(WOA) 09 database; Locarnini et al., 2010), at which most of the SPM was
recovered from the transect. Possibly, the alkenones collected in the SPM
did not represent recently produced material but alkenones synthesized
over several months. Since SPM was collected in July, the warmest month of
the year, the U37K′ would reflect lower temperatures if the
signal also reflected material synthesized in the preceding colder months.
Interestingly, U37K′-derived SSTs of sedimenting particles
also show major discrepancies compared to satellite SSTs, i.e., somewhat
higher U37K′-derived SSTs were observed from January to
mid-May (differing by around 2–3 ∘C) and lower temperatures from
mid-May to July (differing by up to 4.9 ∘C) (Fig. 4, green line and
open diamonds) at the time of the highest alkenone flux (Fig. 3c). The
underestimation of temperatures by U37K′ in sedimenting
particles in July is consistent with the discrepancy between
U37K′-derived and in situ temperature observed for SPM for the
same time period. The application of the U37K′ SPM calibration
proposed by Conte et al. (2006) also results in a general overestimation (by up
to 2.7 ∘C) of U37K′-derived SSTs in both the SPM and
sedimenting particles (data not shown), suggesting that the difference
between U37K′-derived and in situ temperature is not due to
calibration issues.
Higher U37K′-derived SST in cold periods could perhaps be
attributed to the gradual sinking of alkenones that were produced in
preceding warmer time periods. Similar discrepancies, i.e., U37K′-SSTs overestimating in situ winter temperatures and
underestimating in situ summer temperatures in the surface mixed layer, have
been previously described for alkenones in sediment traps from other subpolar
and midlatitude regions (e.g., Sikes et al., 2005; Harada et al., 2006; Seki
et al., 2007; Yamamoto et al., 2007; Lee et al., 2011). In the Mediterranean,
Arabian Sea and the Pacific, U37K′-SSTs lower than in situ SST
during a high alkenone flux have been attributed to either alkenone production
at the thermocline depth or to nutrient deficiency (e.g., Ternois et al., 1997;
Prahl et al., 2000; Harada et al., 2006; Popp et al., 2006).
A compilation of previous sediment trap studies in the North Atlantic has
shown that the U37K′ export signal produced in surface waters
is not equivalent to the vertically transported U37K′ signal
collected in the underlying sediment traps or accumulating in surface
sediments (Rosell-Melé and Prahl, 2013). In the current study, the
U37K′-SST value obtained for the surface sediment at St 1, ca.
10.7 ∘C (Fig. 5), corresponds well with annual mean SST from WOA09
of 9.4 ∘C (Locarnini et al., 2010) but is higher than the
U37K′-derived temperature of the flux-weighted average of our
sediment trap data (7.1 ∘C; Table 3). This difference seems mainly
due to the anomalously low U37K′-derived temperatures at the
time of high alkenone fluxes. These discrepancies could result from (1) a
bias from advected or resuspended alkenones by oceanic currents masking the
local pattern of export production from overlying surface waters (e.g., Prahl
et al., 2001), as has been previously noted in the NE Atlantic
(Rosell-Melé et al., 2000); (2) an unusual subsurface production of
alkenones in the summer of 2011 leading to a cold bias for that year only; or
(3) selective degradation of alkenones when they are sedimenting on the sea
floor (e.g., Hoefs et al., 1997; Rontani et al., 2013).
Proxy-derived temperatures at St 1 in the northern part of the Iceland Basin in sedimenting particles and surface sediment and measured
temperature data from satellite observations (AVHRR, NOAA) and from the
climate database WOA09 (Locarnini et al., 2010).
Temperature (∘C)
U37K′
TEX86
TEX86L
TEX86L
LDI
Measured
0–200 m
SPM July 2011, 5 m
10.8
13.4
11.1
n.d.
n.d.
SMP July 2012, 20 m
12.4
14.4
8.8
n.d.
3.4
Satellite July 2011
11.3
Satellite July 2012
12.9
Flux-weighted mean
7.1
8.5
14.5
11.7
-2.7
Surface sediment
10.7
9.2
14.0
11.4
-1.3
WOA09 annual mean 0 m
9.4
WOA09 annual mean 0–200 m
8.7
n.d.: not detected
The calculation of sinking velocities for alkenones can be done following the
approach of Fischer and Karakas (2009) and Mollenhauer et al. (2015) and uses
the offsets between minimum and maximum temperatures recorded in the
calculated U37K′ temperatures and SST. Maximum derived
temperatures are obtained for sampling periods 4 (5–23 September 2011) and 14
(26 February–15 March 2012), while the maximum satellite SSTs
are in the months June and July (Fig. 4 and Table S2). The minimum
alkenone-derived temperature is during sampling period 19
(24 May–10 June 2012), and minimum satellite SSTs are in February–April 2012
(Fig. 4 and Table S2). Based on this, average sinking velocities (0–1850 m)
for alkenones are ca. 25–30 m day-1, which is substantially lower
compared to the sinking rates of alkenones in the filamentous upwelling region
off Cape Blanc (Müller and Fischer, 2001). However, our estimates are
quite uncertain as alkenone-derived temperatures do not show a clear seasonal
trend compared to the seasonal SST trend (Fig. 4). Furthermore, an offset of
more than 2 months between alkenone production and their fluxes recorded at
1850 m water depth seems in contrast with the similar timing of alkenone
flux patterns and net primary production (derived from OceanColor Web;
Behrenfeld and Falkowski, 1997) over this period (Fig. 3a, c).
In surface waters in the Norwegian–Iceland seas, the abundances of
coccolithophore communities are usually higher during the high-bloom period
(summer) than during the low-bloom period (late summer and fall) (Baumann et
al., 2000). Furthermore, high alkenone fluxes were also previously
observed from April to June, with a rapid decline until August, in 1989 in
the NE Atlantic (Rosell-Melé et al., 2000). Consequently, the increased
flux of alkenones in spring likely reflects the spring bloom.
U37K′-derived SSTs at the peak flux of alkenones thus likely
reflect spring and early summer temperatures, in agreement with previous studies
from high-latitude sites (Sikes et al., 1997; Ternois et al., 1998;
Rosell-Melé et al., 2000; Sicre et al., 2005, 2006; Conte et al., 2006;
Hanna et al., 2006). Degradation during transport in the water column or in
the oxic sediment layer is expected to result in higher
U37K′-derived SSTs, since the C37:3 has a higher
degradation rate than C37:2 (Prahl et al., 1988, 2003; Hoefs et al.,
1998; Gong and Hollander, 1999), and this is indeed what we observe in the
surface sediment compared to the flux-weighted mean (Table 3). An alteration
of alkenones in the sea floor may thus explain the mismatch between surface
sediment signal and flux-weighted mean signal. Finally, it is important to
keep in mind that the data obtained with the sediment trap only provides a
snapshot in time, while the surface sediment stores information collected
over decades to centuries. Thus, the offset of the weighted average
U37K′-derived SSTs may be just a particular feature for the
year 2011 and not representative of what happened over the last few
centuries.
To test the effect of seasonality and diagenetic alkenone alteration around
Iceland, we compared U37K′-SST signals from all surface
sediments with annual mean and seasonal SSTs (derived from the WOA09
database; Locarnini et al., 2010) (Fig. 6a; color code as in Fig. 1).
U37K′-derived SSTs show a good linear correlation with annual
mean SSTs, although absolute temperature values are higher at each station,
with temperature differences ranging from 1 to 4 ∘C (Fig. 6a),
generally higher than the calibration error, i.e., 1.5 ∘C (Müller
et al., 1998) and with the highest deviations for the northernmost stations.
When we compared U37K′-derived temperature values with SST
from different seasons, the best fit is obtained with the summer mean SSTs
(Fig. 6b). This is in agreement with peak alkenone fluxes recorded in our
sediment trap during late spring and early summer. Thus, the sedimentary signal
of U37K′-SST around Iceland seems in general to reflect the
maximum production season of alkenones.
Crossplots of surface-sediment-proxy-derived temperatures
(U37K′, TEX86, TEX86L,
TEX86L 0–200 m and LDI) with annual and seasonal mean
temperatures (only the best seasonal correlations are shown) from the WOA09
database. Regression lines are represented as black lines, and diagonal black
dashed lines show the 1:1 correlation. Different colors indicate
different station locations, as in Fig. 1.
TEX86
GDGTs in the marine environment are likely biosynthesized by Thaumarchaeota
(Sinninghe Damsté et al., 2002), which are omnipresent in the global ocean,
including the polar regions (e.g., Hoefs et al., 1997; DeLong et al., 1998;
Schouten et al., 2000). TEX86L was developed for polar oceans
in order to improve the correlation between TEX86 and SST (Kim et al.,
2010), but a recent study has shown that TEX86 is still suitable as well
(Ho et al., 2014). The TEX86L-SST estimates in the SPM around
Iceland showed a highly variable relationship with in situ temperatures,
showing temperatures up to 6 ∘C higher around Iceland during 2011
(Fig. 2a), while for the SPM transect, the TEX86L-SST
temperatures were up to 7 ∘C lower compared to summer temperatures
at 50 m water depth obtained from the WOA09 database (Fig. 2b). Even higher
offsets, both positive and negative, up to 11 ∘C, were obtained with
TEX86-SST estimates (Fig. 2a, b). A reason for the poor correspondence
of TEX86-derived temperatures with in situ and satellite temperatures
could be a depth habitat effect, since Thaumarchaeota can thrive deep in
the marine water column (Karner et al., 2001; Herndl et al., 2005), although
they tend to have their highest cell numbers at depths < 200 m (e.g.,
Karner et al., 2001). We also applied a specific TEX86 SPM calibration
proposed by Schouten et al. (2013), but temperatures did still show
significant offsets with in situ temperatures (data not shown).
Part of the mismatch may be due to the fact that Thaumarchaeota are smaller
in cell size than the 0.7 µm pore diameter of the SPM filters
(Könneke et al., 2005) and thus may not be quantitatively captured on the
GFFs (Ingalls et al., 2012), possibly affecting the TEX86 values.
However, other studies have shown comparable TEX86 values obtained with
both 0.7 and 0.2 µm pore diameter filters (e.g., Herfort et al.,
2007) or good correspondence with depth (Schouten et al., 2012) or seasonal
(Pitcher et al., 2011) profiles of isoprenoidal GDGT concentrations from
0.7 µm pore diameter filters and thaumarchaeotal rRNA gene
abundances from 0.2 µm pore diameter filters. Thus, the filter size
is unlikely to have affected TEX86 values. Another issue may be that we
analyzed saponified SPM filters, combining both intact and core (non-intact)
GDGT-based lipids. In the natural environment, core lipid GDGTs are derived to a substantial portion from dead cells and may thus represent a fossil
signal from other areas or represent an integrated annual temperature signal.
Lipp and Hinrichs (2009) showed
notable differences in derived temperatures using core vs. intact polar
lipid (IPL) GDGTs from marine sediments. Usually, TEX86-derived temperatures
are higher for IPL GDGTs than for core GDGTs, as was observed in SPM from the
Arabian Sea (Schouten et al., 2012); thus, reduced TEX86-derived SSTs
from the SPM transect may related to core-GDGT contributions. However, this
does not fully explain the dissimilarities observed in the SPM around
Iceland, and thus we lack a clear explanation.
Regarding sedimenting particles, TEX86L-derived SSTs (Fig. 4,
blue line and open circles) were all much higher (up to ca. 9 ∘C)
than satellite SSTs. Reduced differences (up to ca. 5 ∘C higher than
satellite SSTs) were obtained when temperature values were estimated using
the TEX86L 0–200 m calibration (Kim et al., 2012b) (Fig. 4,
red line and open circles and dashed purple line). Interestingly, differences
in temperature decreased significantly when TEX86-derived temperature
and satellite-derived SST were compared (Fig. 4; dark blue line and filled
circles), particularly during times of low GDGT fluxes (Fig. 3d). During
times of high GDGT fluxes, TEX86-SST were lower than satellite SST by up
to 4.6 ∘C, which may suggest that the temperature signal is not
derived just from surface waters. This is supported by TEX86 temperature
values from SPM collected at St 1 during both cruises; TEX86-derived
temperatures from the surface waters are slightly higher than the satellite
SSTs, and significantly higher than the TEX86 values derived from the
material collected in the same months in the sediment trap at 1850 m water
depth. We observed notable differences in estimated temperatures when we used
different calibrations, obtaining better results with the TEX86
calibration (Kim et al., 2010). Similar findings were made by Ho et
al. (2014), who applied TEX86L and TEX86 in different
polar and subpolar regions, such as the Pacific sector of the Southern Ocean
and the Subarctic Front in the North Pacific. Lateral transport of GDGTs is
not likely to have an effect on TEX86 temperatures since isoprenoid
GDGTs are less susceptible to long-distance advection than alkenones
(Mollenhauer et al., 2008; Shah et al., 2008; Kim et al., 2009a). Short-term
degradation has also been shown to have no significant impact on the TEX86
(Schouten et al., 2004; Kim et al., 2009b). Terrigenous GDGTs are also
unlikely to be the reason for the offset in estimated temperatures around
Iceland, based on the low values of the BIT index (< 0.01) (Weijers et
al., 2006, 2009) and the low correlation (R2 < 0.08) between the BIT
index and TEX86 values (cf. Schouten et al., 2013). Comparison of the
flux-weighted mean TEX86 value with surface sediment at St 1 shows
similar values, i.e., 8.5 and 9.2 ∘C using TEX86-SST, 14.5 and
14.0 ∘C using TEX86L-SST, and 11.7 and 11.4 ∘C
for TEX86L 0–200 m, suggesting no alteration of the GDGT
signal during transport to the sea floor (Table 3).
As with alkenones, the sinking velocities for GDGTs can be estimated by
comparing TEX86 values in the sediment trap with observed SST. Maximum
TEX86-derived temperatures were observed for sampling periods 11–17
(5 January–6 May 2012) and minimum temperatures for sampling periods 4 and
18 (5–23 September 2011 and 6–24 May 2012, respectively) (Fig. 4 and
Table S2). Following the method of Fischer and Karakas (2009)
and Mollenhauer et al. (2015), an offset between the production of GDGTs and
their fluxes at 1850 m water depth of 4–6 months would result in
estimated average sinking velocities (0–1850 m) of ca. 10–15 m d-1,
slower than that for the alkenones. However, it should be noted that this
estimate is highly uncertain, as TEX86 temperatures do not show a clear
seasonal trend in comparison to SST (Fig. 4).
GDGT fluxes were high during July, September and October 2011, followed by
May and June 2012 (Fig. 3d), and showed similar patterns to bulk sediment flux
and primary production (Fig. 3a, b). Similar GDGT flux patterns, i.e., high
fluxes at times of high primary productivity, have been
observed in the Arabian Sea (Wuchter et al., 2006), the Santa Barbara Basin,
off the coast of southern California (Huguet et al., 2007), and the upwelling
region off Cape Blanc in Mauritania (Mollenhauer et al., 2015). This was explained by a more
efficient transport of thaumarchaeotal cells, and thus GDGTs, to deeper
waters by the packaging activity of zooplankton thriving after a phytoplankton
bloom. This could be also the case in the northern Iceland Basin, where the
bulk sediment flux may act as an important mechanism for transporting these
lipids to the seafloor. However, the fact that highest fluxes are observed in
late summer does not mean that the annual TEX86 signal here also
represents summer temperatures, as previously suggested by Ho et al. (2014)
for surface sediments from the Arctic, northern Pacific and Southern Ocean,
since the flux-weighted mean TEX86 value from the sediment trap, and the
TEX86 value from the underlying sediment are both similar to annual mean
SST (Table 3).
TEX86- and TEX86L-derived SST in the surface sediments
distributed around Iceland correlate with WOA09 annual mean SSTs (Fig. 6c,
e), although they do show a substantial offset, varying from 1 to
4.7 ∘C. A similar fit is obtained with winter mean temperatures
(Fig. 6d, f), whereas the correlation with summer mean temperatures is
substantially poorer (data not shown). This latter observation agrees with
the idea that the highest GDGT flux during summer does not automatically
result in a TEX86 signal, which records late summer temperatures
(Fig. 3d). This is in contrast with observations by Ho et al. (2014), who
showed anomalously high SST estimates in surface sediments from the Arctic,
northern Pacific and Southern Ocean, and obtained the best correlation of
TEX86-SSTs with summer SSTs.
To test if the sedimentary TEX86 signal around Iceland mainly
reflects subsurface temperature waters as suggested for some other regions
(e.g., Huguet et al., 2007; Lopes dos Santos et al., 2010; Kim et al., 2012a,
b), we compared TEX86L 0–200 m temperature estimates (Kim et
al., 2012b) with the temperature of the upper 200 m of the water column
based on WOA09. We obtained a better correspondence with both annual
and winter mean temperatures (Fig. 6g, h), with differences ranging from 0.5
to 3.5 ∘C. This suggests that TEX86-derived signals in the
surface sediments around Iceland may reflect subsurface (i.e., 0–200 m)
temperatures.
LDI
Long-chain alkyl diols, either the 1,13- and 1,15-diols involved in the LDI
or the 1,14-diols produced by Proboscia diatoms (Sinninghe
Damsté et al., 2003) and Apedinella radians (Rampen et al.,
2011), were below the detection limit in SPM sampled around Iceland in summer
2011. In the SPM sampled during the 2012 transect, small amounts of long-chain 1,15-, 1,14- and 1,13-diols were detected. This suggests that July is
not a period of high productivity for long-chain diol producers around
Iceland. However, long-chain 1,13- and 1,15-diol mass fluxes were relatively
high during July, September and October 2011 and from May to July 2012 (Fig. 3e), suggesting that diol producers were present, although not at the time,
depths or exact locations as where the SPM was sampled. This suggests a
patchy distribution of diol producers. Indeed, it has been observed that
diatom distribution and composition around Iceland is highly variable and
strongly influenced by different environmental variables and particularly by
summer sea surface temperature (Jiang et al., 2001).
Interestingly, the fluxes of 1,13- and 1,15-diols were always much lower than
C28 and C30 saturated and monounsaturated 1,14-diol fluxes, as
well as 3 orders of magnitude lower than those of alkenones and GDGTs.
This indicates that 1,13- and 1,15-diols and their producers are not abundant
in this environment. The presence of C28 and C30 saturated and
monounsaturated 1,14-diol fluxes suggests that Proboscia diatoms
have bloomed in late summer and autumn and late spring and summer. This is further
supported by the identification of C27 and C29 mid-chain hydroxyl
methyl alkanoates in the sedimenting particles (data not shown), which are
also biomarker lipids from Proboscia diatoms (Sinninghe Damsté
et al., 2003). Interestingly, trace amounts of both C28 and C30
1,13-diols have been identified in Proboscia species (Rampen et al.,
2007), and the relatively high abundance of saturated and monosaturated
1,14-diols, combined with a similar flux pattern as that of the 1,13 and
1,15-diols, suggests that Proboscia may also be a source for the
1,13- and 1,15-diols in this area.
Where LDI values could be calculated for the SPM, temperatures were
substantially lower than satellite SSTs (Fig. 2b), exceeding the calibration
error of 2 ∘C (Rampen et al., 2012). For the sediment trap, LDI
values were not always calculated due to the nonquantifiable amount of
C30 1,15-diol. For cases where it was possible, the temperature values
were, like the SPM, much lower than satellite temperatures (Fig. 4, brown
line and open squares; Table 3). The eukaryotic phytoplankton generally
responsible for the production of 1,13- and 1,15-diols are likely
eustigmatophyte algae, autotrophs living in the upper photic zone (Volkman et
al., 1992; Rampen et al., 2012), and on a global scale, the LDI correlates
best with late summer and early autumn SST (cf. Rampen et al., 2012). Thus, a
contribution from colder deep water is unlikely to explain the low
temperatures observed with the LDI. A similar observation is made for the
LDI-derived SSTs in the surface sediments around Iceland which are always
lower than annual mean SST, even when compared with the coldest season, i.e., winter mean SST (Fig. 6i, j). Furthermore, there is no correlation of LDI
values with SST. Also in the surface sediments, relatively low abundances of
1,13- and 1,15-diols compared to 1,14-diols were observed. The mismatch of
LDI values with temperature as well as the low abundances of long-chain 1,13-
and 1,15-alkyl diols reinforce the hypothesis that Proboscia diatoms
seem to be at least a partial source of 1,13- and 1,15-diols in the Iceland
region. This suggests that the LDI may not be applicable in this region.
Therefore, we advise that, if 1,14-diols dominate the distributions of long-chain alkyl diols, the LDI should be applied with great caution.