Global distribution patterns of hydroxy glycerol dialkyl glycerol tetraethers

Organic Geochemistry 57 (2013) 107–118

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Global distribution patterns of hydroxy glycerol dialkyl glycerol tetraethers C. Huguet a,⇑, S. Fietz d, A. Rosell-Melé a,b,c a

Institut de Ciència i Tecnlogia Ambientals, Universitat Autònoma de Barcelona Bellaterra, Catalonia, Spain Department of Geography, Universitat Autònoma de Barcelona Bellaterra, Catalonia, Spain c Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Catalonia, Spain d Department of Earth Sciences, Office 2014a, Chamber of Mines Building, Stellenbosch University, 7600 Stellenbosch, Western Cape, South Africa b

a r t i c l e

i n f o

Article history: Received 25 September 2012 Received in revised form 22 January 2013 Accepted 22 January 2013 Available online 8 February 2013

a b s t r a c t Archaea are ubiquitous in mesophilic and extremophilic environments. Variations in lipid composition of their unique tetraether membrane allow them to maintain integrity and permeability in moderate to extreme environmental conditions. The change in the number of cyclic moieties in their membrane lipids is argued to be an adaptation to ambient temperatures, which is used to estimate past water surface temperature via the TEX86 index. A new class of GDGTs with a hydroxylation in one of the alkyl chains has recently been described in marine sediments. Here we report that these hydroxy-GDGTs are widespread and abundant in mesophilic marine and lacustrine environments. Moreover we observe increasing hydroxy-GDGT contributions towards higher latitudes and lower water temperatures. A significant correlation between the relative abundance of hydroxy-GDGTs and temperature is observed in surface sediments. As these compounds are found both in modern and downcore samples we suggest that the hydroxy-GDGTs could be included in the GDGT paleoproxy tool kit. Ó 2013 Elsevier Ltd. All rights reserved.

1. Introduction Archaea are single celled microbes whose unique 16S rRNA gene sequence sets them apart as the third domain of life (Woese et al., 1990). While some Archaea are extremophile, mesophiles inhabit a wide variety of aquatic (e.g. DeLong, 1992; Fuhrman et al., 1992; Murray et al., 1998; Massana et al., 2000; Karner et al., 2001; Teira et al., 2006; Herndl et al., 2008; Zink et al., 2010) and terrigenous (e.g. Hershberger et al., 1996; Pearson et al., 2004; Leininger et al., 2006; Auguet et al., 2010) environments. Populations of Archaea in many marine environments are dominated by marine Thaumarchaeota, formerly known as Crenarchaeota Group I, (Brochier-Armanet et al., 2008). Archaea synthesize unique isoprenoid ether membrane lipids (Derosa et al., 1986; Derosa and Gambacorta, 1988; Gabriel and Chong, 2000; Gliozzi et al., 2002). The simplest structure reported is archaeol, a glycerol dialkyl diether with C20 isoprenoid chains (Kates, 1972). Archaeol and hydroxyarchaeol diethers are often used to trace the presence of methanogens (e.g. Sprott et al., 1990; Hinrichs et al., 1999; Pancost et al., 2005). The glycerol dialkyl glycerol tetraethers (GDGTs) present two C40 chains joined by two glycerols (e.g. I–VI, Fig. 1). Some GDGTs contain up to 8 cyclopentane moieties, presumably providing a better packaging of the membrane at higher temperatures and allowing Archaea to maintain their membrane in a liquid crystalline state and reduce their proton permeabilisation ⇑ Corresponding author. Tel.: +34 93 5812488. E-mail address: [email protected] (C. Huguet). 0146-6380/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.orggeochem.2013.01.010

rate (Gabriel and Chong, 2000; Gliozzi et al., 2002). The changes in the number of cyclic moieties are the base for the definition of the TEX86 water surface temperature proxy (Schouten et al., 2002). An even more complex core structure composed by a C80 H-shaped core and two glycerols, named H-GDGT, was reported for thermophilic Euryarchaeota (Morii et al., 1998). The reported H-GDGTs contain up to 4 cyclopentane moieties (Schouten et al., 2008a). Recently, mono- and dihydroxy-GDGTs have been reported to occur in marine sediments (Liu et al., 2012). The described hydroxy-GDGTs contain up to 2 cyclopentane moieties and have been identified both in core and intact forms (Lipp and Hinrichs, 2009; Liu et al., 2012). The physiological function of a hydroxy group is not known, but in diethers it has been postulated to alter the cell membrane properties, either extending the polar head group region or creating a hydrophilic pocket (Sprott et al., 1990). It has also been suggested that the hydroxylation of the biphytanyl moiety may result in enhanced membrane rigidity (Liu et al., 2012), but further work is needed to understand their biophysical role. Here we investigate the global geographical occurrence of hydroxy-GDGTs with 0– 2 cyclopentane moieties (Structures VII–IX, Fig. 1), and the existence of a relationship of their distribution with ambient temperature.

2. Material and methods 2.1. Samples A homogenized sediment sample from the Fram Strait (MSM05/ 05-712, Svalbard western continental margin, 78°54.940 N,

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Fig. 1. Structures and m/z values of protonated molecules [M+H]+ found in this study. Structures illustrate Archaea tetraethers previously identified for mesophile Archaea (GDGTs I–VI) (Hopmans et al., 2000) and proposed hydroxy-GDGT structures (GDGTs VII–IX) (based on Lipp and Hinrichs (2009) and Liu et al. (2012)). Only one of the proposed hydroxy-GDGT isomers is shown, see Liu et al. (2012) for other structural isomers.

6°46.040 E, 1490 m depth) was used in order to identify the second set of lipids (compounds VII–IX in Figs. 1 and 2) observed in most of our chromatograms after the usually scanned GDGTs (compounds I–VI in Figs. 1 and 2). Other samples from our archives were chosen in order to illustrate the wide geographical and environmental distribution of hydroxy-GDGTs (Fig. 3). A total of 77 samples including water column (both filtered and trap sample material), surface and downcore sediments samples (covering glacial and interglacial cycles) from freshwater and marine locations were included in this study. Sample locations can be found in Fig. 3a and details in Table 1. Water samples in the Arctic Ocean were taken in 2008 across the Nordic Seas and about 20–60 l were filtered with 0.7 lm GFF filters (Table 1, #1–8). For Mediterranean water samples between 40 and 80 l of water were sequentially filtered through a 0.7 lm GFF and a 0.2 lm DuraporeÒ Millipore filter (Table 1, #9–10). One sample (Table 1, #11) was taken from surface waters (fluorescence maximum) in February 2007 at ca. 1 km off Chipana Bay within the Humboldt Current (Rossi et al., 2012). All filters were kept frozen until extraction. Sediment trap material was obtained from 2 lakes, Lake Baikal (Russia) and Lake Van (Turkey). In Lake Baikal, sediment trap material was collected from 7 sequential traps deployed in the North Basin (Table 1, #12) and another 7 from the South Basin (Table 1, #13) during 2001–2002 (see Fietz et al., 2007 for trap details). The sediment trap material was freeze dried immediately after recovery of all traps in June 2002. The data from the 7 sequential traps of each respective basin were averaged in this study. In Lake Van sediment material (Table 1, #14) was gathered from an integrating trap deployed near the lake bottom allowed to settle and freeze dried (see Huguet et al., 2011 for trap details).

Surface sediment samples (0–1 cm) were collected from the Arctic Ocean (Table 1, #15–17), Fram Strait (Table 1, #18–21), Mediterranean (Table 1, #22–24), from various sites across the oceans at low latitudes between 33°S and 33°N (Table 1, #25– 38) as well as from Southern Ocean (Table 1, #39–52). Multicorers were stored frozen (20 °C) on board and during transport and sub-sampled and freeze dried after returning to the laboratory. The occurrence of hydroxy-GDGTs was also investigated in sediment cores with 25 samples of various ages (Table 1, # 53–77). Mixed samples over several depths from the Arabian Sea (Table 1, #56) and the Drammensfjord (Table 1, #67) used as standards in an intercalibration study for the TEX86 paleothermometer (Schouten et al., 2009) were also included to ascertain compounds were not a laboratory contamination. Two averages over 27 samples in the northeast Atlantic (first average including the H2 event, ca. 22.6–20 ka BP and the second from ca. 20–14.7 ka BP, site MD012461, Peck et al., 2006; Table 1, #54–55) were included, as well as averages over 6–16 samples, respectively, from glacial and interglacial cycles spanning from ca. 400–0 ka BP from the Subantarctic Southern Ocean (Martinez-Garcia et al., 2009; (Table 1, #58–65)). An average of 9 samples from 1.06–0.96 Ma was also included from site ODP 665 near the equator off the African coast (Table 1, #57) as well as averages over 3–12 samples from glacial, interglacial and transitional periods in Lake Baikal North Basin (Fietz et al., 2007; Table 1, #68–73). Averages were used instead of single values to account for the randomness of downcore sample selection and to reduce the error introduced by using proxy-derived values as SST references, since no instrumental data are available for the downcore samples. Single downcore samples available from pilot studies in Lakes Yamozero (Table 1, #66), Bourget (Table 1, #74), Banyoles (Table 1, #76) and Chapala (Table 1, #77) were also included.

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c

1300

100 m/z 743

Relative Abundance

80

OH O

O

O

O

HO

60

m/z 1300

OH

m/z 1208

m/z 1226

40 1282 20

743

1208 1226

1318,31

0 600

I

a

700

800

900

1000

1100

1200

1300

m/z

Arctic Ocean 78.8ºN

V

VII

Relative Intensity

VIII IX

BPC

II

m/z 1300 III

m/z 1318 m/z 1298

V

IV

m/z 1316 m/z 1296 m/z 1314

b

V

I

Southern Ocean 56.6 ºS VII

Relative Intensity

VIII IX

BPC

II

m/z 1300

III

m/z 1318 V

m/z 1298 m/z 1316

IV

m/z 1296 m/z 1314 6

7

8

9

10

11

12

13

14

15

16

17

18

Time (min) Fig. 2. Example chromatograms of high latitude samples. Base peak chromatogram (BPC; mass range 1017.6–1318.9 m/z) and six mass chromatograms for [M+H]+ m/z 1300, 1318, 1298, 1316, 1296 and 1314 for surface sediment samples from (a) Arctic Ocean (78.8°N, 5°E) and (b) Southern Ocean (68,73°S, 164.8°E). (c) Shows the APCI mass spectrum of hydroxy-GDGT VII with three main fragments M18 Da (loss of hydroxy group as H2O), M74 Da (loss of glycerol unit) (Hopmans et al., 2000) and an additional hydroxyl (as H2O) loss of 18 Da. The 743 m/z fragment corresponds to the acyclic biphytane chain.

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Hydroxy-GDGT index 1 (%) 0

a

b

5

10

15

20

90 60

Latitude

30 0 -30 -60 -90

Hydroxy-GDGT index 2 (%)

c

Latitude

d

-60

Fig. 3. Worldwide hydroxy-GDGT (%) distribution. Relative contribution of hydroxy-GDGT (%) was calculated using Index 1 (a and b) and Index 2 (c and d). Circle sizes indicate the hydroxy-GDGT relative abundance with smallest dots indicating minima and largest dots indicating maxima (0–20% in map a, and 0.6–10% in map c). Circles are coded according to sample type, with black for surface sediments, chessboard-pattern for sediment traps, dotted for water samples and grey for downcore sediments.

2.2. Extraction Freeze dried and ground Fram Strait composite box core sediment (82.8 g) was Soxhlet extracted for 24 h with a mixture 1:1 (v:v) of dichloromethane (DCM) and methanol (MeOH) (e.g. Huguet et al., 2010). The two samples from the Drammensfjord and Arabian Sea were extracted using a mixture of DCM and MeOH (7:1; v:v) also with a Soxhlet for 24 h (see Schouten et al., 2009 for details). For all other samples, 0.1–5 g of freeze dried sediment or trap material and water filters were microwave extracted with 10– 30 ml of DCM:MeOH (3:1, v:v) (Kornilova and Rosell-Melé, 2003). The temperature in the extraction vessels of the microwave was increased to 70 °C over 5 min, held at this temperature for another 5 min, and then allowed to decrease to 30 °C. The solvent extracts were decanted, their total volume was reduced under vacuum, and then filtered through a glass pipette filled with glass wool and sodium sulfate to remove residual water and particles. 2.3. Fractionation The Fram strait sediment total lipid extract was separated into apolar, core-GDGT and intact-GDGT (glycol- and phosphor-GDGTs) fractions over a silica column as suggested by Lipp and Hinrichs

(2009). In short, the solvents used were DCM to elute the apolar fraction, DCM:acetone (3:1 v:v) for the core-GDGTs and DCM:MeOH (1:1 v:v) followed by MeOH to recover the intactGDGT fraction. The fractions containing the core- and intactGDGTs were divided in three further sub-fractions. One was prepared for high performance liquid chromatography–mass spectrometry (HPLC–MS) analysis, another was saponified and the last was hydrolyzed. Saponification or base hydrolysis was achieved by adding 2 ml of 1 M KOH:MeOH to the sample and refluxing at 70 °C for 1 h. The mixture was acidified to pH 2 by adding hydrochloric acid (HCl). Acid hydrolysis was achieved by adding, 2 ml of 5% HCl in MeOH (v:v) to the dry extract in a vial, which was then flushed with N2, capped and left for 4 h at 70 °C. On completion, the sample was left to cool, then equal parts of DCM and MilliQwater were added and the DCM fraction was collected. The remaining acid solution was extracted three additional times with DCM and the organic extracts were combined. The total DCM extract was rinsed six times with MilliQ water in order to remove traces of acid (e.g. Huguet et al., 2010) and blown to dryness with N2. For the other samples, different fractionation protocols were used depending on the sample, place and person extracting them as they were not originally intended for this study. Arctic water (Table 1, #1–8), Arctic surface sediment (Table 1, #15–21), western

Table 1 Detailed sample information: Sampling station, region, sample type, coordinates, measured or estimated water surface temperature (°C) and hydroxy-GDGT relative abundance (%) calculated using indices 1–6 (see text for details). Type

Site name

Latitude (°N)

Longitude (°E)

SST

Hydroxy-GDGTIndex 1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55

Water Water Water Water Water Water Water Water Water Water Water S-Trap S-Trap S-Trap Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Surf-S Downcore-S Downcore-S Downcore-S

Arctic Arctic Arctic Arctic Arctic Arctic Arctic Arctic Mediterranean Mediterranean Humboldt current Lake Baikal Lake Baikal Lake Van Arctic Arctic Arctic Arctic Arctic Arctic Arctic Mediterranean Mediterranean Mediterranean Pacific Atlantic Arabian Sea Atlantic China Sea Indian Ocean Indian Ocean Pacific Atlantic Atlantic Atlantic Atlantic Atlantic Pacific Southern Ocean Southern Ocean Southern Ocean Southern Ocean Southern Ocean Southern Ocean Southern Ocean Southern Ocean Southern Ocean Southern Ocean Southern Ocean Southern Ocean Southern Ocean Southern Ocean Pacific Atlantic Atlantic

75.05 75.00 74.94 74.00 72.97 69.02 64.98 62.04 42.52 39.92 21.31 54.45 51.70 42.77 87.07 87.01 86.53 80.50 79.10 78.80 78.80 40.91 40.58 40.13 32.83 31.67 27.71 18.08 6.16 5.38 4.93 1.30 1.20 3.67 5.18 5.78 29.92 32.59 42.87 45.76 50.75 53.29 56.51 57.15 59.70 60.77 61.05 61.50 63.00 64.97 65.40 68.73 58.00 51.75 51.75

10.46 8.42 1.53 20.01 16.56 8.64 1.85 2.48 3.07 2.18 70.11 109.07 105.02 38.63 104.66 145.71 152.10 5.90 4.60 5.00 5.60 2.08 3.54 2.20 119.98 75.42 34.68 21.03 112.21 90.35 73.28 133.60 11.88 37.72 10.44 10.75 35.66 73.65 8.97 177.15 85.69 89.55 23.01 53.99 171.36 115.98 159.59 23.00 89.49 143.80 91.17 164.80 140.00 12.92 12.92

0.0 5.4 2.5 0.5 0.3 5.6 9.0 10.7 24.6 26.4 17.0 4.6 4.2 11.8 0.6 1.5 1.5 0.6 1.4 1.2 1.2 18.5 18.8 19.1 16.0 24.6 25.6 23.0 28.5 28.7 28.8 26.0 25.7 27.4 25.7 25.8 21.9 15.7 9.8 10.9 7.7 6.8 0.4 2.1 3.2 2.6 0.5 0.5 2.2 0.8 0.0 1.2 9.2 16.1 15.2

11.8 11.8 7.1 19.8 14.5 14.5 12.2 8.4 0.0 0.0 7.9 19.0 18.2 0.0 9.7 7.8 7.9 7.9 7.6 8.4 9.9 1.9 1.7 1.5 2.8 3.1 4.3 0.9 2.7 2.4 2.2 1.4 1.5 2.6 2.6 1.7 2.9 2.7 13.6 3.9 5.0 6.9 9.3 12.5 6.1 5.5 5.7 9.3 13.9 3.8 8.9 7.8 13.6 8.9 6.9

Hydroxy-GDGTIndex 2 7.5 10.1 9.7 8.7 3.4

4.1 4.4 4.3 5.9 2.5 1.8 1.5 2.7 0.0

0.1 1.9 1.4

2.3

4.0 3.6 5.2 3.3 3.8 4.1 2.8 3.5

Hydroxy-GDGTIndex 3 26.7 27.5 17.7 35.5 30.3 25.2 26.2 20.7 0.0 0.0 14.4 34.7 33.6 0.0 21.6 19.5 20.4 19.4 18.4 21.5 25.8 4.1 3.6 3.2 5.4 7.4 8.8 1.6 5.8 4.4 4.6 2.5 3.3 5.6 5.8 3.4 4.9 6.3 27.3 9.7 12.1 17.2 23.1 28.8 15.5 13.6 14.4 23.2 27.8 10.2 20.8 18.7 24.2 19.5 15.3

Hydroxy-GDGTIndex 4 16.2 20.6 22.2 21.1 7.7

10.0 10.1 10.4 14.9 4.6 3.5 3.0 5.7 0.0

0.2 3.7 2.8

5.9

10.1 8.8 16.1 8.6 10.2 9.6 6.6 7.3

Hydroxy-GDGTIndex 5 18.1 17.3 10.8 31.6 21.8 25.8 19.1 12.7 0.0 0.0 15.6 30.3 28.0 15.4 11.8 11.7 12.2 11.9 12.3 14.2 3.6 3.3 3.0 5.9 5.4 8.4 2.6 5.2 6.0 4.8 3.4 2.8 4.9 5.0 3.8 6.8 4.8 21.9 6.4 8.0 10.4 13.7 18.4 9.3 8.6 8.7 13.5 22.1 5.6 13.6 12.0 24.0 14.4 11.3

Hydroxy-GDGTIndex 6 12.2 16.4 14.8 13.0 6.0

6.6 7.4 6.8 9.0 5.4 3.8 3.3 5.3 0.0

0.2 4.2 2.8

C. Huguet et al. / Organic Geochemistry 57 (2013) 107–118

Sample

3.9

6.2 5.7 7.2 5.3

6.9 5.0 6.7 111

(continued on next page)

7.8 12.1 13.7 0.2 3.3

10.3

5.4 7.3

2.6

15.8 10.5 11.7 0.7 2.5

9.0

12.7 6.1

16.2 6.8 8.3 11.3 15.6 10.7 6.8 5.5 5.9 6.6 0.1 1.4

5.0

2.2

3.6

3.7

3.7 3.4

7.2

7.8

16.2

16.9 12.2 23.4 29.4 21.2 29.8 19.0 8.9 4.5 6.5 8.8 9.7 8.5 5.2

6.8

11.1 13.5 24.6 17.2 9.7 14.4 13.6 19.7

Hydroxy-GDGTIndex 5 Hydroxy-GDGTIndex 4

4.2 4.9 13.6 17.6 33.5 22.0 15.7 18.8 19.1 23.6 3.5 6.4

1.8 2.8 6.4 8.2 16.3 10.6 6.3 8.8 8.5 11.9

Hydroxy-GDGTIndex 3 Hydroxy-GDGTIndex 2 Hydroxy-GDGTIndex 1 SST

27.7 19.2 12.7 7.9 11.2 7.9 10.8 7.4 11.1 8.7 13.6 13.0 12.3 4.7 3.8 5.1 7.0 3.4 10.3 7.7 13.9 19.2 53.18 19.67 8.90 8.90 8.90 8.90 8.90 8.90 8.90 8.90 50.23 10.40 108.91 108.91 108.91 108.91 108.91 108.91 5.87 5.87 2.75 103.00

Longitude (°E) Latitude (°N)

16.05 2.95 42.92 42.92 42.92 42.92 42.92 42.92 42.92 42.92 65.00 59.67 53.96 53.96 53.96 53.96 53.96 53.96 45.73 45.73 42.12 20.33 Arabian Sea Atlantic Southern Ocean Southern Ocean Southern Ocean Southern Ocean Southern Ocean Southern Ocean Southern Ocean Southern Ocean Lake Yamozero Drammensfjord Lake Baikal Lake Baikal Lake Baikal Lake Baikal Lake Baikal Lake Baikal Lake Bourget Lake Bourget Lake Banyoles Lake Chapala 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77

Site name Type

Downcore-S Downcore-S Downcore-S Downcore-S Downcore-S Downcore-S Downcore-S Downcore-S Downcore-S Downcore-S Downcore-S Downcore-S Downcore-S Downcore-S Downcore-S Downcore-S Downcore-S Downcore-S Downcore-S Downcore-S Downcore-S Downcore-S

Sample

Table 1 (continued)

7.0

C. Huguet et al. / Organic Geochemistry 57 (2013) 107–118

Hydroxy-GDGTIndex 6

112

Pacific Southern Ocean surface sediment (Table 1, #44–47 + 49– 52) extracts were redissolved in 100 ll of hexane:DCM (1:1, v:v) prior to manual injection in a Thermo Surveyor HPLC equipped with a Lichrosphere silicon dioxide column (4.6  250 mm, 5 lm; Teknokroma) and a stainless steel inline filter (2 lm pore size). Compound class fractionation was achieved by running n-hexane (0–2.7 min, apolar fraction containing alkanes and alcohols), DCM (2.7–5.7 min, intermediate fraction containing amino acids), acetone (5.7–9.2 min; polar fraction containing GDGTs) and n-hexane (9.2–13.5 min final fraction to rinse the column) with a 2 ml/min flow. In Lake Van (Table 1, #14) and Mediterranean (Table 1, #22–24) samples, the total lipid extract was divided into apolar, intermediate and polar fractions using a small column filled with activated silica and using hexane:DCM (9:1; v:v), hexane:DCM (1:1; v:v) and DCM:MeOH (1:1; v:v) as eluents, respectively. Both trap samples from Lake Van (Table 1, #14) and water samples from the Mediterranean (Table 1, #22–24) were hydrolyzed as described for the Fram Strait sample, in this case to possibly increase yield by combining intact and core GDGT fractions (c.f. Huguet et al., 2010). Most samples were divided into apolar and polar fractions using activated silica gel or activated alumina that was sequentially eluted with hexane:DCM (9:1 v:v) and DCM:MeOH (1:1, v:v), respectively, (e.g. Escala et al., 2007; Schouten et al., 2007; Huguet et al., 2010). These were Lake Baikal sediment traps (Table 1, #12– 13), surface sediments from the temperate to tropical regions in the Pacific, Atlantic, Indian Ocean and China Sea (Table 1, #25– 38), surface sediment samples from the Atlantic and eastern Pacific sections of the Southern Ocean (Table 1, #39–43 + 48) as well as downcore sediment from NE Atlantic (Table 1, #54–55), Arabian Sea (Table 1, #56), Drammensfjord (Table 1, #67) and Lake Baikal (Table 1, #68–73). Then the polar fraction was redissolved in hexane:n-propanol (99:1, v:v) and filtered through a 0.45 lm PTFE filter (Advantec). Samples from the core in the subantarctic Southern Ocean (Table 1; #58–65) were not fractionated.

2.4. GDGT instrumental analysis Analysis was performed using a Dionex P680 HPLC system coupled to a Thermo Finnigan Triple Stage Quadrupole (TSQ) Quantum Discovery Max MS with an atmospheric pressure chemical ionization (APCI) interface set in positive mode. Extracts were eluted using a Tracer Excel CN column (0.4 cm diameter, 20 cm length, 3 lm particle size; Teknokroma) equipped with a precolumn filter and a guard column. The elution program was modified from Escala et al. (2007). Samples were eluted with hexane/n-propanol at 0.6 ml/min. The amount of n-propanol was held at 1.5% for 4 min, and then increased gradually to 5.0% during 11 min, increased to 10% during 1 min and held at 10% for 4 min, then decreased to 1.5% during 1 min and held at 1.5% for 9 min until the end of the run. The parameters of the APCI were set as follows to generate positive ion spectra: corona discharge 3 lA, vaporizer temperature 400 °C, sheath gas pressure 49 mTorr, auxiliary gas (N2) pressure 5 mTorr and capillary temperature 200 °C. Detection of GDGTs was done in single ion monitoring (SIM) mode of [M+H]+ ± 0.5 m/z units to increase signal to noise ratio (Schouten et al., 2007). The isoprenoid GDGTs (Iso-GDGTs) were routinely monitored at m/z 1302, 1300, 1298, 1296 and 1292. Samples were measured in full scan (350–1500 m/z) to determine the real [M+H]+ of the observed VII–XI peaks. Additionally, in order to establish whether peaks VII–IX belong to the Iso-GDGT group (Fig. 2) we fragmented the compounds. Fragmentation was achieved through MS–MS analysis with the same HPLC–MS setup with the APCI interface set in positive mode. Collision gas pressure was set to 2 mTorr and collision energy 35 V for optimal fragmen-

C. Huguet et al. / Organic Geochemistry 57 (2013) 107–118

tation spectrums. The scan range was 500–1330 m/z and the fragmentation targeted 2 masses, 1302 and 1300 m/z. After peaks VII–IX were identified as hydroxy-GDGTs, a sub-set of 35 samples was re-analyzed to ensure that the latitudinal distribution shown by the relative abundance of hydroxy-GDGT did not differ between scanning the protonated ions ([M+H]+, m/z 1318, 1316, and 1314) and dehydrated ions ([M+H18]+, m/z 1300, 1298 and 1296) of hydroxy-GDGTs. 2.5. Exact mass determination The exact masses of compounds VII and VIII were measured to confirm their identification in a hydrolyzed extract of the Fram Strait sample. The extract was analyzed using an HPLC (1200RR Agilent) with a Tracer Excel CN column (0.4 cm diameter, 20 cm length, 3 lm particle size; Teknokroma) coupled to a microTOF-Q (Bruker Daltonics) MS using an APCI interface The conditions of the interface were set to positive ionization, capillary current 4200 V, corona discharge 5000 nA, vaporizer temperature 300 °C, nebulizer pressure (N2) 3.8 bars, dry gas flow (N2) 9.0 l/min and dry gas temperature 250 °C. 2.6. Water surface temperature data assessment Temperature data for the Arctic Ocean water samples were obtained from the ship’s thermosalinograph at the time of water collection. Sea surface temperatures (SSTs) of the Mediterranean Sea water samples and all surface sediments were extracted from the World Ocean Atlas 2005 (WOA05) mean annual data set (Schlitzer, 2011). For sediment trap and downcore samples surface temperature estimates were obtained using the TEX86 or UK37 indices. For the marine settings, except for the subantarctic Southern Ocean, temperatures were estimated using the TEXL86 or TEXH 86 according to Kim et al. (2010) calibration. Subantarctic Southern Ocean values were calculated using UK37 according to Prahl and Wakeham (1987). The TEX86 in lakes was calculated according to Powers et al. (2010). 3. Results and discussion 3.1. Lipid identification During routine chromatographic analysis of GDGTs (Fig. 2) to measure the TEX86 and BIT indices (Schouten et al., 2002; Hopmans et al., 2004), a group of later eluting peaks (VII–IX) was often observed (Fig. 2). To establish the identity of these peaks we focused our analytical efforts in a sample from the Fram Strait that contained them in high amounts. Compounds VII–IX were identified as archaeal GDGTs because they show a fragmentation pattern consistent with Iso-GDGTs (Hopmans et al., 2000), i.e. they lose the characteristic H2O and glycerol fragments (see VII example Fig. 2c). As the masses are similar to previously described IsoGDGTs (peaks II–IV), the longer retention times must result from either a chemical (increased polarity) or physical (different three dimensional configuration) retention. A group of later eluting GDGT compounds, H-GDGTs, was previously reported in thermophilic Euryarchaeota (Morii et al., 1998; Schouten et al., 2008a). However, when a hot vent sample from Loki’s Castle Arctic Mid-Ocean Ridge (Jaeschke et al., 2012) known to contain H-GDGTS with 0–4 moieties was run, the retention times did not overlap with the observed VII–IX peaks. Moreover the MS–MS fragmentation did not show the characteristic H-GDGT fragmentation patterns (Morii et al., 1998; Knappy et al., 2009). Some intact polar GDGTs (intact GDGTs) have also been observed to elute after the core GDGTs when measured in APCI mode

113

(Pitcher et al., 2009). In order to rule out this possibility we fractionated the Fram strait sample into apolar, core-GDGT and intact-GDGT fractions (Lipp and Hinrichs, 2009). When the three fractions were scanned, only the one containing the core-GDGT presented the target compounds (VII–IX). As intact hydroxyGDGTs have also been reported (Liu et al., 2012), we did a basic and acid hydrolysis on the last two fractions in order to ensure intact-GDGT breakdown. Hydrolysis treatments did not yield the target hydroxy-GDGTs from the intact-GDGT fractions which were then discarded from later analysis. While saponification of the core-GDGTs resulted in no changes on peak distribution or abundance, the acid hydrolysis resulted in a 30% reduction of peak VII without changes in retention time, thus indicating that the structure is somewhat susceptible to acid hydrolysis but that its polarity does not change. As the later eluting peaks were neither intact- nor H-GDGTs, we postulate that they are the recently described hydroxy-GDGTs (Liu et al., 2012). Lipp and Hinrichs (2009) provided some tentative evidence of a 2 Gly-hydroxy-GDGT with a hydroxy on a tertiary carbon atom with a mass of 1316 Da in an early lipid study. This was confirmed by a recent work that reported the presence of both mono and dihydroxy-GDGTs with 0–2 cyclopentane moieties (Liu et al., 2012). Indeed when the Fram Strait sample was measured in full scan, the [M+H]+ of the peaks was found to be 1318 m/z (peak VII), 1316 m/z (peak VIII) and 1314 m/z (peak IX) respectively, though the latter is present in very low amounts (Fig. 2). To confirm the identification of the target lipids we measured the exact masses of compounds VII and VIII (compound IX concentration was too low to perform the analysis) using GDGT-I as a reference (Fig. 1). The measured exact mass of GDGT-I was 1302.31840 Da, which corresponds to the elemental composition of C86H172O6 with an exact mass 1302.32267 Da with an instrumental uncertainty of 5 ppm. Based on their mass and general compositional rules, compounds VII and VIII were estimated to have the formulas C86H172O7 and C86H170O7 with theoretical masses of 1318.317584 Da and 1316.301934 Da. The measured masses were within 5 ppm of those theoretical values with masses 1318.3139 Da and 1316.2962 Da, respectively. Therefore peaks VII–IX were identified as hydroxy-GDGTs with 0–2 cyclopentane moieties. The position of the hydroxyl group in the alkyl chains was not determined, and thus only putative structures are given (Fig. 1; Liu et al., 2012). Based on the extreme lability displayed by hydroxy-diethers, hydroxy-GDGTs are thought to be extremely labile (Lipp and Hinrichs, 2009; Liu et al., 2012). As we were able to measure hydroxy-GDGTs at the 1318, 1316 and 1314 m/z selected ions in a wide range of samples (37 samples included in hydroxyGDGTIndex 2, 4 and 6, Table 1) and find only 30% loss of hydroxyGDGTs during acid hydrolysis, we suggest that the tertiary hydroxyl groups are less labile than those of the hydroxydiethers. This may be due to the protection of the hydroxy group by the tetraether macrocycle. We propose that the late elution of these molecules in the HPLC column, beyond the usual GDGTs monitoring time range (e.g. Schouten et al., 2007), explains why despite hydroxy-GDGTs being ubiquitous and abundant in all our samples they were only recently reported in 12 marine sediments (Liu et al., 2012). In our laboratory their analysis is facilitated by using a faster (higher flow and polarity gradient) HPLC program (Escala et al., 2007, 2009) than the one commonly employed (e.g. Schouten et al., 2009). 3.2. Lipid source organisms The isoprenoid structure of the hydroxy-GDGTs indicates that they must belong to Archaea as this lipid structure is specific for

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this organism domain (Woese et al., 1990). Even though hydroxyarchaeol diethers are often used to trace the presence of methanogens (e.g. Sprott et al., 1990; Hinrichs et al., 1999; Pancost et al., 2005), the widespread distribution of hydroxy-GDGTs in oxic environments (Fig. 3; Liu et al., 2012) suggests that their origin can also be partially attributed to mesophilic non-methanogenic Archaea. This is in agreement with Liu et al. (2012) who found them in an extremophile Euryarchaeota culture (Methanothermococcus thermolithotrophicus) but also suggests their presence in Thaumarcheota (Candidatus Nitrosopumilus maritimus) based on mass spectra results by Schouten et al. (2008b). We find hydroxy-GDGTs to be widely distributed in fresh and marine water environments. As Thaumarchaeota are dominant in many marine environments (Auguet et al., 2010; Church et al., 2010), it is likely that the GDGTs VII–IX we observe in the sediments are preferentially derived from this group. Hydroxy-GDGTs have also been reported for Group I.1a and I.1b Thaumarchaeota in soils (Sinninghe-Damsté et al., 2012), confirming that they are widely distributed in mesophilic environments. Further work is needed to constrain the sources of hydroxyGDGTs.

20

In order to compare the abundance of hydroxy-GDGTs at different study sites with different production levels we calculated a relative abundance index. The relative abundance of hydroxy-GDGT was calculated as follows:

Hydroxy-GDGTIndex1;2 ð%Þ P ð hydroxy-GDGTsÞ P ¼ 100  P ð hydroxy-GDGTs þ Iso-GDGTsÞ

20

Hydroxy-GDGTIndex 1 (%)

8

4

a

8

0

5

10

12

15

20

25

30

-5

4

c 10

15

20

15

20

25

30

25

30

(ºC)

y=-0.12X + 4.3 (R2=0.78, n=19 p<0.001)

8

4

d

0 5

10

12

Hydroxy-GDGTIndex 2 (%)

8

Water surface temperature (ºC)

5

Water surface temperature

y=-0.18X + 5.7 (R2=0.46, n=22)

0

0

(ºC)

Marine Water Column Marine Surface Sediment Marine downcore sediment Freshwater downcore sediment

-5

b

0

Water surface temperature

Hydroxy-GDGTIndex 2 (%)

12

4

-5

0

y=-0.24X + 8.3 (R2=0.59, n=38 p<0.001)

16

y=-0.32X + 10.6 (R2=0.42, n=72)

12

0

ð1Þ

where R hydroxy-GDGTs includes compounds VII–IX and R IsoGDGTs includes compounds I–VI (Fig. 1). We calculated an Index 1 (hydroxy-GDGTIndex 1 (%)) that uses the abundance of VII, VIII and IX monitored in the 1300, 1298 and 1296 m/z SIM ranges as in Liu et al. (2012). A hydroxyGDGTIndex 2 was also calculated in fewer samples where the abundance of VII, VIII and IX was estimated using a SIM method with the addition of selected ions 1318, 1316 and 1314 m/z. The two indices are not always equivalent (Table 1) and this may be due

Marine Water Column Marine Surface Sediment Marine downcore sediment Freshwater downcore sediment

16

Hydroxy-GDGTIndex 1 (%)

3.3. Worldwide distribution

-5

0

5

10

15

20

25

30

Water surface temperature (ºC)

Fig. 4. Correlation between sample site’s annual mean surface temperature and relative abundance of hydroxy-GDGTs, calculated with Index 1 (a and b) and Index 2 (c and d). All samples were included in graphs (a) and (c) but only surface sediments are shown in graphs (b) and (d). Sea and lake surface temperatures were instrument or WOA05 derived for modern samples (water and surface sediments, respectively). Surface temperatures for downcore samples were reconstructed based on the TEX86 and UK37 (see Section 2). Regression line and 95% confidence intervals are shown.

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to changes in the MS conditions along the extended measuring period (from 2007–2012), nonetheless the general latitudinal distribution prevails (Fig. 3). In our survey of water, surface sediment and downcore sediment samples both hydroxy-GDGTIndex 1 and 2 (%) are latitude dependent (Fig. 3): lower hydroxy-GDGT relative abundances are found approaching the equator and increase polewards (Fig. 3). The lowest hydroxy-GDGT relative abundances (0–8%) were found at tropical and mid latitudes between 45°N and 30°S, and up to 20.5% at higher latitudes (Fig. 3). Previously reported hydroxy-GDGTIndex 1 values reach a maximum of 8% (Liu et al., 2012), probably due to their lack of samples from high latitudes. While many environmental parameters like insolation, temperature or nutrient availability vary with latitude, previous work on GDGTs clearly singled out temperature as the most likely driving factor for their distribution (e.g. Gliozzi et al., 2002; Schouten et al., 2002; Kim et al., 2010; Powers et al., 2010). The same is likely the case for hydroxy-GDGTs’ percentage distribution.

Hydroxy-GDGTIndex 3;4 ð%Þ P ð hydroxy-GDGTsÞ ¼ 100  P ð hydroxy-GDGTs þ CrenarchaeolÞ

20

10

a -5

y=-0.62X + 20.1 (R2=0.70, n=38 p<0.001)

40

Hydroxy-GDGTIndex 3 (%)

y=-0.77X + 24.5 (R2=0.57, n=72)

30

30

20

10

b

0 0

5

10

15

20

Water surface temperature 25

25

30

-5

0

(ºC)

5

10

15

20

Water surface temperature

25

30

(ºC)

y=-0.35X + 10.9 (R2=0.79, n=19 p<0.001)

25

Marine Water Column Marine Surface Sediment Marine downcore sediment Freshwater downcore sediment

20

ð2Þ

where R hydroxy-GDGTs includes compounds VII–IX and crenachaeol is compound VI in Fig. 1. In this case Index 3 denotes hydroxy-GDGTs measured in the 1300, 1298 and 1296 m/z SIM ranges and Index 4 those measured in the 1318, 1316 and 1314 m/z SIM ranges. Using crenarchaeol, which is not included in the TEX86 index, eliminates possible biases of the calculated indices 1 and 2 by other Iso-GDGTs with a clear temperature dependence.

Marine Water Column Marine Surface Sediment Marine downcore sediment Freshwater downcore sediment

0

Hydroxy-GDGTIndex 4 (%)

Even though other driving factors cannot be ruled out, temperature is significantly correlated to Index 1 and 2 (Fig. 4). To investigate further the potential correlation with temperature, an additional index using crenachaeol instead of the sum of all the Iso-GDGTs was also used to estimate relative abundance:

20

y=-0.44X + 13.5 (R2=0.49, n=37)

Hydroxy-GDGTIndex 4 (%)

Hydroxy-GDGTIndex 3 (%)

40

3.4. Potential relation to temperature

15

10

5

15

10

5

c

d

0

0 -5

0

5

10

15

20

Water surface temperature (ºC)

25

30

-5

0

5

10

15

20

25

30

Water surface temperature (ºC)

Fig. 5. Correlation between sample site’s annual mean surface temperature and relative abundance of hydroxy-GDGTs, calculated with Index 3 (a and b) and Index 4 (c and d). All samples were included in graphs (a) and (c) but only surface sediments are shown in graphs (b) and (d). Sea and lake surface temperatures were instrument or WOA05 derived for modern samples (water and surface sediments, respectively). Surface temperatures for downcore samples were reconstructed based on the TEX86 and UK37 (see Section 2). Regression line and 95% confidence intervals are shown.

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A third index was calculated to include only the compounds with similar carbon skeleton: Hydroxy-GDGTIndex 5;6 ð%Þ P ð hydroxy-GDGTsÞ ¼ 100  P ð hydroxy-GDGTs þ GDGT-I þ GDGT-II þ GDGT-IIIÞ

ð3Þ

where R hydroxy-GDGTs includes compounds VII–IX (Fig. 1). In this case Index 5 denotes hydroxy-GDGTs measured in the 1300, 1298 and 1296 m/z SIM ranges and Index 6 those measured in the 1318, 1316 and 1314 m/z SIM ranges. To evaluate the potential relationship between the hydroxyGDGT distribution and temperature we calculated the level of correlation between the Indices and measured or estimated temperature (Figs. 4 and 5). When all the data are used, significant, but weak correlations are found with temperature. As data are not normally distributed correlations were checked with a Spearman Rank analysis and were found to be significant with p < 0.01 as follows:

ST ¼ 0:32  hydroxy-GDGTsIndex 1 þ 10:6 ðR2 ¼ 0:42; n ¼ 72; p < 0:01Þ

ð4Þ

1

ST ¼ 0:18  hydroxy-GDGTsIndex 2 þ 5:7 ðR2 ¼ 0:46; n ¼ 37; p < 0:01Þ ST ¼ 0:77  hydroxy-GDGTsIndex 3 þ 24:5 ðR2 ¼ 0:57; n ¼ 72; p < 0:01Þ

¼ 37; p < 0:01Þ

ð7Þ

ST ¼ 0:45  hydroxy-GDGTsIndex 5 þ 16:7 ðR2 ¼ 0:37; n ¼ 72; p < 0:01Þ

ð8Þ

ST ¼ 0:26  hydroxy-GDGTsIndex 6 þ 9:2 ðR2 ¼ 0:36; n ¼ 37; p < 0:01Þ

ð9Þ

The scatter observed is certainly partly due to the wide sample range considered (saline and fresh water lake samples, surface 1

Y = 0.009 X + 0.39 (R2=0.69, n=35, p< 0.001)

Y = 0.015 X + 0.19 (R2=0.83, n=35, p< 0.001)

0.8

OH-TEX86 index-1

TEX86 proxy-1

ð6Þ

ST ¼ 0:44  hydroxy-GDGTsIndex 4 þ 13:6 ðR2 ¼ 0:49; n

0.8

0.6

0.4

0.2

0.6

0.4

0.2

a

0 -5

b

0 0

5

10

15

20

25

30

-5

0

Water surface temperature (ºC) 1

5

10

15

20

25

30

25

30

Water surface temperature (ºC) 1

Y = 0.013 X + 0.32 (R2=0.89, n=19, p< 0.001)

Y = 0.017 X + 0.32 (R2=0.90, n=19, p< 0.001)

0.8

OH-TEX86 index-2

0.8

TEX86 proxy-2

ð5Þ

0.6

0.4

0.6

0.4

0.2

0.2

c

0 -5

d

0 0

5

10

15

20

Water surface temperature (ºC)

25

30

-5

0

5

10

15

20

Water surface temperature (ºC)

Fig. 6. Correlation between sample site’s annual mean surface temperature and TEX86 (Schouten et al., 2002) are shown in panels a and c, and OH-TEX86 (see text for details) are shown in panels (b) and (d). Panels (a) and (b) show results from the simple SIM scan method (1302,1300,1298, 1296 and 1292 m/z, 1), panels c and d show data from samples scanned with the extended SIM method (adding 1318, 1316 and 1314 m/z, 2). Sea surface temperatures were WOA05 derived regression line and 95% confidence intervals are shown.

C. Huguet et al. / Organic Geochemistry 57 (2013) 107–118

117

sediments and downcore samples from glacial and interglacial periods; Fig. 3, Table 1). Other reasons for the scatter may be lower presence of hydroxy versus Iso-GDGTs preventing detection. For example, no hydroxy-GDGTs were detected in Mediterranean water samples but they were present in the underlying accumulated sediment, therefore the amount of water filtered must have been insufficient to detect them. Hydroxy-GDGTs were also not found in Lake Van trap samples, however this is a soda lake that hardly presents any Iso-GDGTs (Huguet et al., 2011). There is also some scatter associated to downcore sediments, as in this case the correlation was done with proxy reconstructed temperatures, and thus the degree of error is much greater than with instrumental or satellite data. Proxy temperature reconstructions show different errors, 1.5 °C for L the UK37 , from 2 °C TEXH 86 to 4 °C TEX86 in marine settings and 3.6 °C for TEX86 in lakes (Kim et al., 2010; Powers et al., 2010). Additional data dispersion may have been introduced by using annual mean temperature estimates as Archaea lipid production can present a seasonal cycle that can affect the estimated TEX86 temperature (e.g. Murray et al., 1998; Huguet et al., 2006, 2007; Leider et al., 2010). However if only the surface sediments are used, all indices show an even stronger significant correlation with temperature (Figs. 4 and 5). Spearman Rank analysis showed correlations to be significant with p < 0.001. The lowest correlation was found for hydroxy-GDGTIndex 5 and the highest for hydroxy-GDGTIndex 4:

depending on the SIM scan used, Fig. 6) when the hydroxy-GDGTs are added to the TEX86. This indicates that the OH-TEX86 may potentially improve temperature estimations (Fig. 6). Moreover the correlations of OH-TEX86 and temperature display higher slopes (Fig. 6) and could thus increase the resolution of the temperature estimates, especially at the colder end of the correlation line.

ST ¼ 0:24  hydroxy-GDGTsIndex 1 þ 8:3 ðR2 ¼ 0:59; n

Acknowledgements

¼ 38; p < 0:001Þ

ð10Þ

ST ¼ 0:12  hydroxy-GDGTsIndex 2 þ 4:3 ðR2 ¼ 0:78; n ¼ 19; p < 0:001Þ

ð11Þ

ST ¼ 0:62  hydroxy-GDGTsIndex 3 þ 20:1 ðR2 ¼ 0:70; n ¼ 38; p < 0:001Þ

ð12Þ

ST ¼ 0:35  hydroxy-GDGTsIndex 4 þ 10:9 ðR2 ¼ 0:79; n ¼ 19; p < 0:001Þ

ð13Þ

ST ¼ 0:34  hydroxy-GDGTsIndex 5 þ 13:1 ðR2 ¼ 0:53; n ¼ 38; p < 0:001Þ

4. Conclusions We report the widespread occurrence of hydroxy-GDGTs with 0–2 cyclopentane moieties. These hydroxy-GDGTs are ubiquitously distributed in aquatic mesophile environments and are especially abundant in cold, high latitude settings. We postulate that these lipids may help mesophile Archaea to expand and adapt towards low temperature environments by modifying the composition of their membrane. The relative abundance of hydroxy-GDGTs is significantly correlated to surface water temperatures in surface sediments. Moreover a weak correlation is also observed between the relative abundance of hydroxy-GDGTs downcore and proxy estimated temperatures. We propose that the relative abundances of hydroxy-GDGTs could help to improve GDGT related proxies to estimate past water temperatures at the lower range that are encountered in higher latitudes. A much larger dataset is needed to validate the present indices and interpretations.

We thank Gemma Rueda, Dr. Sze Ling Ho, Natalia Nuñez, Dr. Marine Escala, Dr. Vicky Peck, Dr. Alfredo Martínez-García, Anna Barrera, Dr. Joan Albert Sanchez-Cabezas and Dr. Ana Carolina Ruiz Fernández, for providing sediment samples. Núria Moraleda and Joan Villanueva are thanked for technical assistance. Dr. Andrea Jaeschke is thanked for providing H-GDGT containing sample. We also want to thank Prof. Stefan Schouten and Dr. Rienk Smittenberg for constructive comments on an earlier version of this manuscript. We want to thank two anonymous reviewers that also contributed to the improvement of the manuscript. This work was financed through the Juan de la Cierva grants from the Spanish government to C.H. and S.F. The work leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under Grant Agreement No. [252659].

ð14Þ Associate Editor—Stefan Schouten

ST ¼ 0:16  hydroxy-GDGTsIndex 6 þ 6:7 ðR2 ¼ 0:65; n ¼ 19; p < 0:001Þ

ð15Þ

These results confirm that even though other parameters may have an effect, temperature is the main driving factor for the hydroxyGDGT distribution. Hydroxy-GDGTs may represent up to 20% of the total Iso-GDGTs in areas with temperatures below 0 °C (Index 1, Fig. 4), this suggest that their presence may be important for cell membrane structure in cold environments. In order to investigate further the potential of hydroxy-GDGTs in temperature proxies we calculated the TEX86 (Schouten et al., 2002) and compared the results to a newly proposed OH-TEX86 index. The OH-TEX86 index is based on the addition of hydroxyGDGTs in the denominator where they would represent cold growing conditions together with the compound II (Fig. 1) as follows: ðGDGT-III þ GDGT-IV þ GDGT-VIÞ OH-TEX86 ¼ P ð hydroxy-GDGTs þ GDGTs-II GDGT-III þ GDGT-IV þ GDGT-VIÞ ð16Þ

where numbers correspond to those in Fig. 1 and R hydroxy-GDGTs includes compounds GDGT-VII–IX. In this case we observe an increase of the r2 values (from 0.69 to 0.83 and from 0.89 to 0.90

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