Archaeal lipids record paleosalinity in hypersaline systems

Organic Geochemistry 42 (2011) 1147–1157

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Archaeal lipids record paleosalinity in hypersaline systems Courtney Turich ⇑, Katherine H. Freeman Department of Geosciences, Pennsylvania State University, University Park, PA 16802, USA

a r t i c l e

i n f o

Article history: Received 30 July 2010 Received in revised form 28 May 2011 Accepted 4 June 2011 Available online 12 June 2011

a b s t r a c t We present an ecologically based biomarker method for estimating past salinity, especially in hypersaline conditions. The relative amounts of acyclic diether and tetraether membrane lipids synthesized by Archaea correlate with salinity from 0–250 practical salinity units (psu) in modern settings. We examined the preservation of this lipid biomarker–salinity relationship in ancient sedimentary organic matter using samples from two sequences of marls and diatomites deposited just prior to the Messinian Salinity Crisis. Salinity estimates were consistent with expected absolute salinity, as well as the amplitude of variations leading up to the Messinian Salinity Crisis. This lipid biomarker approach to salinity reconstruction complements existing paleosalinity proxies because (i) Archaea survive and thrive over a broad salinity range, well beyond that of haptophyte algae and other plankton which form the microfossil record and (ii) it provides fine salinity resolution for the wide range broadly defined as hypersaline. With the proxy, there is the potential to provide novel insights into salinity variation within desiccating basins in climatically sensitive seas (e.g. Dead Sea, Permian Delaware Basin), evolution of brines, timing of onset of hypersaline conditions and evaporite deposition. Ó 2011 Elsevier Ltd. All rights reserved.

1. Introduction Progress in the development of paleosalinity proxies highlights the importance of salinity for ocean circulation patterns, hydrological variations and climate change on a global scale (Gbaruko et al., 2007; Rohling, 2007; van der Meer et al., 2007, 2008; Sachse and Sachs, 2008). Recent efforts have focused on calibrating the relationship between salinity and the dD of water and alkenone lipids synthesized by haptophyte algae (van der Meer et al., 2007; Sachse and Sachs, 2008).These methods show promise for producing a precise salinity proxy for marine basins, although hydrogen isotope fractionation is also associated with alkenone biosynthesis (Schwab and Sachs, 2009) and growth phase (Wolhowe et al., 2009). Other methods include using a combination of d18O of microfossil carbonate and dD of organic compounds to produce paleosalinity approximations within 1 practical salinity unit (psu) (Rohling, 2007), or using assemblages, chemistry and morphology of microfossils to generate salinity reconstructions (Bollmann et al., 2009; Fielding et al., 2009; Mertens et al., 2009). However, in hypersaline systems where typical marine fauna are absent, other approaches need to be developed. Hypersaline systems can be harbingers and agents of catastrophic changes such as tectonically and hydrologically induced basin isolation (the Messinian Mediterranean, the Great Salt Lake), stagnation and anoxia (Permian Zechstein and Delaware basins). Hypersaline basins ⇑ Corresponding author. Present address: ConocoPhillips 600 N Dairy Ashford Houston, TX 77079, USA. E-mail address: [email protected] (C. Turich). 0146-6380/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.orggeochem.2011.06.002

are also vital to geobiology; Proterozoic hypersaline waters harbored Earth’s earliest fossils (Knoll, 1985). Therefore, calculating paleosalinity across a broad hypersaline range can provide specific conditions of evolving climate systems and early ecosystems. Archaea are ubiquitous microbes in the environment (Delong, 1992; Hershberger et al., 1996; Karner et al., 2001; Beja et al., 2002; Fuhrman, 2002; Ochsenreiter et al., 2002; Sinninghe Damsté et al., 2002a; Herndl et al., 2005; Biddle et al., 2006), thriving across temperature, pH, redox and salinity gradients. Distinct differences in the salinity tolerance of Archaea, from fresh water to hypersalinity, produce shifts in the relative dominance of archaeal groups and thus their lipid distributions. Halophiles appear to produce only diphytanyl glycerol diethers (DGDs) with 43 carbons, including archaeol (Teixidor et al., 1993; Kates, 1996; Grice et al., 1998; Fig. 1, I). Marine Euryarchaeota produce DGDs and glycerol dibiphytanyl glycerol tetraethers (GDGTs) with 86 carbons. GDGTs include an acyclic moiety, as well as ring-containing GDGTs; we reserve use of the term ‘‘caldarchaeol’’ to refer to only the acyclic compound (Fig. 1, II). The cyclic GDGTs are produced by close relatives of the marine Euryarchaeota (acidophiles and thermophiles) and it is not proven whether the marine Euryarchaeota also produce these structures, as do their extremophile relatives (Macalady et al., 2004; DeLong et al., 2006). Marine Crenarchaeota also produce archaeol and caldarchaeol as well as the cyclic counterparts (Gulik et al., 1986; Sinninghe Damsté et al., 2002b; Konneke et al., 2005). Crenarchaeol, with 3 pentacyclic rings and one hexacyclic ring, has been proposed as a diagnostic biomarker for Crenarchaeota in marine and terrestrial environments (Sinninghe Damsté et al., 2002b; Pearson et al., 2004; Weijers et al., 2004).

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C. Turich, K.H. Freeman / Organic Geochemistry 42 (2011) 1147–1157

Fig. 1. Fischer projections of diphytanyl glycerol diether (archaeol, I) and glycerol dibiphytanyl glycerol tetraethers (acyclic caldarchaeol, II) synthesized by Archaea.

The core isoprenoid lipids of Archaea are relatively recalcitrant in sedimentary organic matter (OM), with intact core ether lipids found in Jurassic to Recent sediments and oils (Chappé et al., 1982; Kuypers et al., 2002; Schouten et al., 2003) and biphytane structures in older sediments. The relative abundance of DGD and GDGT lipid biomarker should vary as a function of salinity to reflect the ecologic transitions from marine to hypersaline archaeal populations. Geological preservation of lipid patterns would allow the relative abundance of ether lipids for estimating paleosalinity. To evaluate this potential, we measured GDGT and DGD lipid patterns in suspended particulate matter (SPM) and surface sediments collected from hypersaline, marine, estuarine and fresh waters. Although both planktonic and subsurface archaeal communities produce ether isoprenoid lipids, subsurface Archaea tend to be anaerobic (e.g. ANME, methanogens) and are unlikely to be quantitatively significant in surface sediments. Therefore, we assume the planktonic microbes are most important source of ether lipids used in this study. We also analyzed sedimentary OM deposited in two marginal basins in the late Miocene (ca. 5.8 Ma), just prior to a period of severe evaporation in the Mediterranean. The ecological changes captured by both modern and ancient lipid patterns indicate the relative abundance of archaeol and caldarchaeol may serve as a useful tool in paleosalinity reconstruction. 2. Material and methods 2.1. Sample collection Brackish and marine sample sites represent a variety of nutrient conditions and distances offshore and include both previously collected and new samples collected for this study and for Turich et al. (2007; Table 1). Samples were extracted following the methods in Wakeham et al., 2003 (Fig. 2). Two freshwater samples, from a terrestrial bog (Bear Meadows, Pennsylvania) and Swansgut creek (Virginia), represent low salinity end members. SPM from the oxygenated surface waters of the Black Sea (Wakeham and Beier, 1991) and from Chincoteague Bay, Virginia is from the brackish to marine salinity range (20–30 psu). Marine sites include the Arabian Sea (Lee et al., 1998), Santa Monica Basin (Bidigare et al., 1997), Peru upwelling margin (Pancost et al., 1997), the Equatorial Pacific (Wakeham et al., 1997) and the Bermuda time series site (Conte et al., 2001; Turich et al., 2007). Hypersaline samples were collected at Infersa Saline, an industrial saltern on the western coast of Sicily. Ionic compositions of solar saltern waters were similar to other Mediterranean coastal salt pans and Dead Sea waters (Madigan et al., 2000; Eder et al., 2001;

Ochsenreiter et al., 2002; Oren, 2002). We also collected marine samples from Chincoteague Bay, VA (USA) aboard a Marine Science Consortium Inc. (Wallops Island, VA) vessel in 2003. Salinity was determined by way of brine hydrometer in the salt pans, and Sonde multi-parameter probe (YSI Inc.) in Chincoteague Bay. At both these sites, 3–20 l water were filtered onto 142 mm, pre-combusted glass fiber filters with nominal pore size of 1 lm. While this pore size is large, it is standard for oceanographic sampling for suspended particulate matter for lipid analysis. Inevitably, some individual cells are not collected, although particles will be trapped. All samples were stored on ice until they reached the lab and were then stored at 80 °C. Ion chemistry was determined with ion chromatography (brines) and inductively coupled plasma–atomic emission spectroscopy (ICP–AES; all other samples). Messinian sediments were collected from outcrops of the Tripoli Formation (6.96–5.93 Ma) in central Sicily (Fig. 2, inset), providing high resolution and continuous records spanning the transition from marine to hypersaline conditions that mark the onset of the Messinian Salinity Crisis (MSC; Hilgen and Krijgsman, 1999). We analyzed samples from two sub-basins of the Caltanissetta Basin, the northern Torrente Vaccarizzo (TV) and the southern Serra Pirciata (SP; Butler et al., 1999), both of which are correlated with the more complete Falconara section based on precessional cycles (Bellanca et al., 2001). The TV section spans 6.35–6.02 Ma and incorporates cycles 34–49 (Blanc-Valleron et al., 2002). Laminar gypsum (1.4 m) caps cycle 49. SP spans 6.07–5.93 Ma and includes astrologically correlated cycles 47–52 (6 m), which underlie the Calcare di Base, a massive carbonate bed with replaced gypsum and halite signifying the MSC. 2.2. Sample preparation Rock surfaces were mechanically cleaned prior to ball mill grinding. Lipid extraction and analysis generally followed Schouten et al. (2002). Lipids were extracted from filters and powdered rocks using 9:1 CH2Cl2:MeOH in a Soxhlet apparatus for 24 h. For filters collected from high salinity sites, the organic phase was rinsed with hexane-extracted DI water to remove salts and dried over extracted NaSO4. The total lipid extract from the Messinian sediments was separated into asphaltene and maltene fractions with iso-octane precipitation of asphaltene. We analyzed only the maltene fraction. The solvent lipid extract was separated into three fractions on activated Al2O3 in a glass Pasteur pipette. The eluents were (i) 9:1 hexane CH2Cl2, (ii) 1:1 CH2Cl2:MeOH and (iii) methanol. All archaeal lipids eluted in the second fraction.

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Sicily Infersa salt pans

Torrente Vaccarizzo

Serra Pirciata

60°

60°

g c

d e

30°

j

h

f

i

30° k

0°

0°

b

a

-30°

-30°

-60°

-60°

Scale: 1:213562539 at Latitude 0° Fig. 2. Map of sample sites: (a) Equatorial Pacific, (b) Peru Margin, (c) Santa Monica Basin, (d) Bear Meadows, Pennsylvania, (e) Chincoteague Bay, Virginia, (f) Bermuda time series site, (g) Mediterranean, (h) Infersa salt ponds, Sicily, (i) Messinian outcrops, Sicily and (j) Black Sea. Sample sites with surface sediments include the Arabian Sea, Eq. Pacific, Chincoteague Bay, Black Sea and Infersa salt ponds.

(a)

(b)

(c)

654 + (M+H )

archaeol standard

653 m/z OH

100

93

O

597

OH O

O

O

113

373

155

155

50

373 597 653

0

2

4

time (min)

6

8 600

10 620

640

660

m/z

680

700

0 50

150

250

350

450

550

650

m/z

Fig. 3. (a) HPLC–APCI–MS chromatogram of archaeol standard. (b) HPLC–APCI spectrum of archaeol standard (c) MS–MS daughter scan of archaeol standard.

2.3. Sample analysis 2.3.1. Instrumental conditions Analysis of ether lipids generally followed methods developed by Hopmans et al. (2000) using a Micromass Quattro-II API-III LC/MS/MS. Liquid chromatographic separation of archaeol and GDGTs was achieved with a 2.1  150 mm 3 lm Prevail Cyano column (Alltech, Deerfield, IL, USA) maintained at 30 °C. The mobile phase was an isocratic solution of 100% hexane (5 min), followed by a 45 min linear gradient to 98.2% hexane:1.8% propanol with a flow rate of 0.2 ml/l. In between samples, the column was flushed for 10 min with 75% hexane:25% propanol followed by equilibration (10 min) with the starting mobile phase. Standards and extracted samples were analyzed in selected ion monitoring (SIM) mode restricted to specific retention time windows for DGDs (0–10 min at m/z 600–700) and GDGTs (10– 26 min at m/z 1280–1350). Instrument conditions included: corona voltage 5.5 kV, cone voltage 15 V, source temperature 130 °C, atmospheric pressure chemical ionization (APCI) probe 550 °C. Peak areas were calculated using Masslynx 3.5 software (Micromass, London, UK) based on [M + H]+ and [M + H + 1]+ ions (m/z 653.5–655.4 for archaeol and 1301.5–1303.4 for caldarchaeol).

2.3.2. Archaeol detection via HPLC–MS DGDs and GDGTs differ significantly in polarity, size and volatility (Fig. 1). Typically, intact DGDs are analyzed using gas chromatography (GC) following derivatization (methylation or trimethylsilyation) of the glycerol hydroxyl group, while the larger intact core GDGTs are analyzed using liquid chromatography atmospheric pressure chemical ionization mass spectrometry (LC–APCI–MS). We adapted existing tetraether LC–MS techniques to identify and quantify the most abundant DGD, archaeol, without derivatization and in the same LC–MS sample run as the GDGTs. To identify the retention time and response factor, we used a dilution series of the archaeal standard (1,2-di-O-phytanyl-snglycerol from Avanti Lipids, Alabaster, AL, USA). Dilution series of the 1,2-di-O-phytanyl-sn-glycerol standard ranged in concentration from 0.6 to 750 ng. To compare the DGD and GDGT response factors, we isolated 5 lg of caldarchaeol from sediment in Bear Meadows bog (Centre County, Pennsylvania, USA) using preparative LC. We confirmed the purity of the isolated compound and thereby the reliability of the standard weight, by scanning m/z 100–1400 in APCI mode. The retention time of the archaeol standard was routinely between 4.26 and 4.58 min (Fig. 3a). Its APCI mass spectrum (m/z 653) shows the ion for the protonated molecule (M + H+; Fig. 3b).

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C. Turich, K.H. Freeman / Organic Geochemistry 42 (2011) 1147–1157

3e+4

450 400

300 1.5e+4

250 200

1e+4 150 DGD

5e+3

100

24-Jul-05

17-Jul-05

3-Jul-05

10-Jul-05

26-Jun-05

19-Jun-05

5-Jun-05

12-Jun-05

29-May-05

22-May-05

8-May-05

15-May-05

1-May-05

24-Apr-05

GDGT

0

GDGT Response factor

350 2e+4

50

31-Jul-05

DGD Response factor

2.5e+4

Fig. 4. Response factors for diphytanyl glycerol diether (archaeol) and glycerol dibiphytanyl glycerol tetraether (caldarchaeol) over time.

MS-MS daughter scan of m/z 654 (collision energy 20 eV, scan range m/z 50–700) shows the parent ion (m/z 653) and fragments from the loss of the glycerol (597 Da), cleaving of ether bonds (373 Da) and fragmentation of the isoprenoid chains (e.g. m/z 155 Da, Fig. 3c). Response factors (RFs) for diether standards range from 7000 to ca. 30,000 area/ng; GDGT RFs were typically several of orders of magnitude less, from 90 to 450 area/ng. The far greater RF for diether relative to tetraethers reflects the smaller and more volatile nature of diethers, which are therefore more efficiently ionized via APCI. The minimum detection limit for DGD was 0.1 ng and for GDGT 7.5 ng. The relative response factor varied over time (Fig. 4) and it was necessary to create standard curves for both DGDs and GDGTs during each run cycle. The standard deviation of estimated abundances calculated from duplicate analysis of standards was typically within 30 and we applied this as a mean error to all samples. 3. Results 3.1. Archaeol, caldarchaeol and salinity The LC–MS method allows comparison of the relative abundances of archaeol and GDGTs with a single analysis. Characteristic differences in the relative abundances of archaeol and caldarchaeol between marine and hypersaline environments are illustrated in

(a)

(b)

II I

I

5x Relative Intensity

LC–MS chromatograms (Fig. 5). Marine sites typically contained little archaeol and abundant GDGTs. Hypersaline sites contained predominantly archaeol, although smaller amounts of caldarchaeol were also present and decreased inversely with salinity. Crenarchaeol is generally not detected in hypersaline environments because of a shift in community from marine Crenarchaeota to halophilic Euryarchaeota. Therefore, we chose to compare changes in the relative amounts of archaeol and caldarchaeol and calculated the normalized ratio: [archaeol (A)/archaeol (A) + caldarchaeol (C)]  100 (Table 1). There is significant variability in the relative amounts of acyclic diether and tetraether lipids in the sampled environments, where 100 (A/A + C) ranges from 0.02–19. The lowest values were found in the Black Sea, Equatorial Pacific, Santa Monica Basin and Peru Margin. Intermediate values included SPM from Bear Meadows, shallow Equatorial Pacific and Chincoteague Bay (Watt’s Bay). Highest values (2–19) were found in (i) a tidally flushed stream (Swansgut Creek) as well as (ii) within the Sargasso Sea chlorophyll max. at 210 m depth (6.7), (iii) the Arabian Sea (6.3 and 15.3; 4 m at stations 1 and 4) and (iv) Chincoteague Bay, (15.9, 19 in surface waters). All the values for hypersaline salt ponds were an order of magnitude higher than values from estuarine and marine SPM. Those for the salt ponds increased linearly from 46–72 over a salinity range from 103 to 236 psu. We note, however, that caldarchaeol was not detected in Mono Lake, an alkaline hypersaline (80 psu) lake. Over the range 20–250 psu, there is a strong linear correlation between salinity and the relative amounts of archaeol to caldarchaeol: 100 (A/A + C) = 0.35  salinity 5.37 (R2 0.87, n = 26; Fig. 6). Removing samples with obvious terrestrial influence (sample collected from stream in forested area flowing into Chincoteague Bay) and the anomalous Arabian Sea sample improves the correlation: 100 (A/A + C) = 0.385  salinity 9.675 (R2 0.95, n = 20). Because of the generally poor correlation of the lower salinity fresh and marine samples, the index should not be used to calculate salinity below the hypersaline range, but can be used to corroborate marine vs. hypersaline conditions. Using a correlation with only the four hypersaline samples has an excellent correlation but a high y intercept value (100 (A/ A + C) = 0.192  salinity + 26.012 (R2 0.98). The subsequent salinity calculations at the hypersaline level using this limited calibration are between 15–30 psu less than values calculated using the more inclusive calibration, or between 8% and 20% of salinity in the hypersaline zone. However, the removal of the non-hypersaline samples from the correlation results in negative salinity measurements at 100 (A/A + C) values < 26 and is therefore meaningless at lower salinity values. In order to use the calibration for ancient sedimentary environments, it must be

cyclic GDGTs

200x

II

time Fig. 5. Extracted ion chromatograms of ether lipids from modern suspended particulate matter (SPM) in (a) normal marine salinity, 35 psu (Equatorial Pacific 110 m) and (b) hypersaline salterns (Sicily coast) and archaeal lipid structures I) archaeol and II) caldarchaeol.

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C. Turich, K.H. Freeman / Organic Geochemistry 42 (2011) 1147–1157 Table 1 Suspended particulate matter and sediment sample locality, physicochemical properties and A (archaeol)/C (caldarchaeol) ratio. Location

Collection date

Latitude

AS3 4 AS4 4

19-May-1995 16-May-1995

16.62 17.20

59.80 59.58

Bear Meadows

BMF02

19-Jun-2003

40.73

Black Sea

BS2 30 BS2 70 BS2 100

1-Apr-2003 1-Apr-2003 29-Apr-2003

41.42 41.42 41.42

Bermuda time series

BTS210

6-Nov-2003

Chincoteague Bay

CJF06 WBF02 WBF06 SGF02

9-Jul-2003 21-May-2003 9-Jul-2003 9-Jul-2003

Eq. Pacific

EPS1 EPS1 EPS2 EPS2 EPS2

24-Feb-1992 24-Feb-1992 30-Aug-1992 30-Aug-1992 30-Aug-1992

Mediterranean

Med50 Med75

Infersa salt pans

Suspended particles Arabian Sea

Name

Longitude

Salinity (psu)

Temperature (°C)

Depth (m)

Ion chemistry (g/L) S

Ca

2+

+

K

(A/A + C)  100 Mg

2+

+

Na

Cl

36.38 36.39

27.16 27.08

77.76

0.00

21.80

0

0.00

0.00

0.00

0.00

0.00

0.00

2.4

29.57 29.57 29.57

18.57 20.67 21.09

7.28 8.29 8.47

30 71 100

0.50 0.54 0.54

0.24 0.26 0.28

0.22 0.22 0.24

0.74 0.76 0.84

5.76 5.92 6.52

13.20 13.20 14.80

0.7 0.5 0.5

31.92

64.08

36.63

19.23

210

1.08

0.44

0.44

1.36

11.62

27.20

6.7

37.98 37.91 37.91 38.00

75.43 75.46 75.46 75.44

27.42 30.07 30.67 1.73

30.46 16.13 27.11 19.08

1 0 2 0

0.68 0.84 0.70 0.84

0.32 0.56 0.34 0.36

0.32 0.38 0.34 0.34

1.04 1.06 1.06 1.12

8.22 8.45 8.88 9.24

16.80 0.86 18.80 19.40

19.0 3.3 15.9 9.7

0.00 0.00 0.33 0.33 0.33

140.41 140.41 139.56 139.56 139.56

35.15 35.32 35.13 35.13 35.09

28.28 25.85 24.50 24.50 19.46

39 111 10 33 101

10-May-2003 10-May-2003

43.42 43.42

7.88 7.88

38.25 38.31

13.19 13.10

50 75

1.10 1.14

0.48 0.48

0.46 0.46

1.46 1.46

12.06 12.00

28.80 28.80

2.7 3.8

P26AF P27CF P38CF P48CF

20-May-2002 20-May-2002 20-May-2002 20-May-2002

37.99 37.99 37.99 37.99

12.53 12.53 12.53 12.53

147.73 236.28 175.14 103.14

29.60 25.00 23.40 22.70

0 0 0 0

4.22 6.02 5.03 3.64

1.13 0.42 0.86 0.88

2.01 3.61 2.41 1.52

6.43 11.14 7.84 4.95

48.84 77.66 58.49 33.43

354.44 399.65 277.81 193.28

55.5 72.2 57.4 46.1

Peru Margin

PM075 PM 109

8-Mar-1992 8-Mar-1992

13.50 12.00

76.93 77.98

35.02 35.05

17.80 18.00

10 10

1.6 2.5

Santa Monica Basin

SMB5 40 SMB6 40

2-Feb-1992 12-Apr-1992

34.00 34.00

119.00 119.00

33.29 33.38

14.78 17.65

40 40

2.1 0.1

1-Nov-1994 Fall 1992 7-Jul-2004 May 2003 May 2002

13.25 0.00 37.98 41.4221 37.99

65 140 75.43 29.57 12.53

36.38 35.15 27.42 18.57 147.00

Surface sediments Arabian Sea Eq. Pacific Chincoteague Bay Black Sea sed Infersa salt pan

39 110 15 39 110

4 4

1.0 15.3

0.7 1.1 2.4 0.8 0.5

0.7 7.4 0.1 0.4 59.0

Acrhaeol / (Archaeol + Caldarchaeol) *100

80 2

y = -5.4 + 0.35x R = 0.87

70

suspended particulate matter surface sediment

correlation with all suspended particle samples y = 0.35x - 5.4 R2 =0.87

60

correlation without terrestrially influenced samples* y = 0.38x - 9.7 R2 =0.95

50

40 8 7

30

6 5 4

20

* **

3 2 1

10 *

0 15

* 0

0

50

100

20

150

25

30

200

35

40

250

salinity (psu) Fig. 6. Salinity and relative abundance of archaeol to caldarchaeol from modern marine suspended particulate matter in waters >260 m. Open squares, suspended particles, with star indicating samples with terrestrial influence; solid squares, surface sediments.

capable of providing a possible range of values across the fresh to hypersaline range. The inclusive calibration also encompasses a wide range of environments, from fluvial influenced estuaries

to diverse marine basins, providing a realistic assessment of the range of conditions potentially encountered in the paleorecord. Therefore, we believe the benefits in including the lower

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C. Turich, K.H. Freeman / Organic Geochemistry 42 (2011) 1147–1157

salinity data points in the calibration are worth the cost in accuracy. We term the relationship between archaeol, caldarchaeol and salinity ‘‘ACE’’, the Archaeol (A) and Caldarchaeol (C) Ecometric; ACE = 100 (A/A + C). The clear relationship between salinity and ACE values above normal marine salinity is responsible for much of the excellent correlation. A weak correlation is found for samples from marine and brackish sites (100 (A/A + C) = 0.11  Salinity 1.66, R2 0.16, n = 16), again omitting samples with obvious terrestrial influence and the Arabian Sea sample with an anomalously high amount of archaeol, potentially because of methanogens responsible for temporary fluxes of methane. Temperatures at the sample sites ranged from 14 °C (Santa Monica Basin) to 30 °C (salt ponds). However, there was no correspondence between temperature and ACE over the entire suite of samples, including hypersaline sites. Water ion chemistry obviously largely

(a)

correlates with salinity and major ions (Cl , Mg++, Ca++, Na+ and K+) also exhibit positive correlations with ACE (Table 1), as does total S content. Mg/Ca values correlate poorly with ACE (R2 0.6) because gypsum precipitation removes Ca++ ions from solution in the highest salinity pond (>230 psu). 3.2. Archaeol and caldarchaeol in surface sediments To evaluate the preservation of the lipid–salinity relationship for sediments, we compared the archaeol/caldarchaeol ratio in SPM with five surface sediment samples from the Black Sea, Chincoteague Bay, Arabian Sea, Eq. Pacific and Infersa salt ponds (Table 1). In Chincoteague Bay, sediment ACE (0.1) values are much lower than SPM ACE values. Conversely, the equatorial Pacific sediment ACE values (7.4) are greater than SPM ACE. In the salt pans (59), the Arabian Sea (0.7) and the Black Sea (0.4), sediment ACE

(b) cyclic GDGTs

Relative Intensity

I

I

II 100x

II

time Fig. 7. Extracted ion chromatograms of ether lipids from Serra Pirciata Messinian section at (A) 17.4 m and (B) 19.7 m, at onset of hypersalinity.

18O carbonate -5

‰ v. PDB 1

0

18O carbonate

5

10

20

-5

‰ v. PDB 1

0

5

10

16 14

19 12 18 10 17

8 6

16 4 15 2 14

0 0

10

20

30

40

50

60

0

10

archaeol/ (archaeol + caldarchaeol) *100 0

20

40

60

80

100

120

140

160

calculated salinity (psu)

Laminated Diatomites Laminated red marls dolostone

20

30

40

50

60

archaeol/(archaeol + caldarchaeol) *100

0

20

40

60

80

100

120

140

160

calculated salinity (psu)

Marls

Diatomitic Marly Laminated Calcare di Base silty marl limestone Gypsum

Slump

Fig. 8. Stratigraphy and archaeol/caldarchaeol  100 (ACE) and calculated salinity based on the modern calibration in Torrente Vaccarizzo (right) and Serra Pirciata (left). Stratigraphy reproduced from Bellanca et al. (2001).

C. Turich, K.H. Freeman / Organic Geochemistry 42 (2011) 1147–1157

values are closer to the SPM ACE values. We discount the very high Arabian Sea SPM value as typical because of the anomalously high amount of archaeol. 3.3. Archaeol and caldarchaeol in ancient sediments In order to determine if the relationship between salinity and ACE in modern SPM is evident in ancient material, we analyzed lipids from sedimentary OM deposited during a period of known salinity changes. HPLC–MS chromatograms from Messinian lipid extracts revealed archaeal lipid distributions strikingly similar to those observed in modern environments from marine to hypersaline environments (Fig. 7). In the Torrente Vaccarizzo (TV) section, ACE values range from 1.4 to 6.1 throughout the lower section (1.8–11.8 m) and at 13.9 m, prior to the deposition of laminar gypsum at 15.2 m, the value increases to 47.5 (Fig. 8, right). In the Serra Pirciata (SP) section, ACE was generally higher than in the TV section and exhibited greater fluctuation (Fig. 8, left). At the lowest point of the section (14.1 m), ACE values are 3.7 and increased to 20.5 at 17.6 m. Above17.6 m, values decrease to 11.4 at 18.4 m and to 9.7 at 18.95 m. At 19.55 m and 19.77 m, values increase significantly to 51.4 and 57.2. We used the linear salinity–ACE correlation from modern samples to calculate salinity prior to the onset of the Messinian Salinity Crisis (Fig. 6). In the TV section, the estimated salinity is consistently a brackish ca. 20 psu until just prior to laminar gypsum deposition when the lipid based salinity estimate is ca. 140 psu, more than four times the salinity lower in the section and well within the salinity at which gypsum precipitates (110 psu). In the SP, the estimated salinity in the lowest sample of the section is also in the brackish range, although higher than in TV (25– 28 psu). Salinity increases to nearly 60 psu at 17.6 m, 1.6 times higher than average Mediterranean salinity today (38 psu). Upsection from this salinity increase, the estimated salinity stabilizes at normal marine values (32–36 psu). Finally, at 19.55 m, just below the onset of the MSC, there is an increase in calculated salinity, ranging from briny 140 psu to 160 psu. 4. Discussion 4.1. Origin of lipid–salinity relationship The relationship between archaeal lipid distributions and salinity likely represents a shift from a mixed marine Euryarchaeota and Crenarchaeota community to only Euryarchaeota halophiles, as seen in other saltern waters (Casamayor et al., 2002). Halophilic Euryarchaeota are diverse and active (Ovreas et al., 2003), tolerating salinity up to NaCl saturation (Oren, 2002). Although osmoregulation in halophiles depends in part on lipid polar head groups (Roessler and Muller, 2001; Tenchov et al., 2006), core lipids used in this study are not known to affect osmoadaptation. The freshwater, brackish and marine sites with ACE values from 1–20 are associated with increased nutrients derived from coastal inputs (Swansgut, Watt’s Bay, Arabian Sea), upwelling (Peru Margin, Equatorial Pacific), or seasonal mixed layer shoaling (Sargasso). The Arabian Sea sample may be further compromised by input from extensive coastal sabkhas. The two highest ACE values (15.9, 19) are from the lower portion of the watershed in the estuarine Chincoteague Bay, which receives excessive nutrient input (Primrose, 2004), suggesting a possible link between either nutrients or terrestrial input on archaeal lipid distributions. The presence of caldarchaeol in hypersaline waters is unexpected because halophilic Archaea, including methanogenic halophiles, produce only DGDs. Salt pond water is concentrated

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seawater, so it might be expected that some marine archaeal cells might remain in the high salinity environment. However, the GDGT patterns are completely atypical of marine Archaea, with only a minor amount of crenarchaeol in just one salt pond sample. Crenarchaeota [Marine Benthic Group B (MBGB)] were recently detected (Jahnke et al., 2008) and enriched (Orphan et al., 2008) in hypersaline environments in microbial mats and may be especially dominant in the deeper parts of microbial mats (Robertson et al., 2009). However, this may not explain minor crenarchaeol or caldarchaeol in surface waters. Runoff may also deposit terrestrially produced caldarchaeol, although such contributions are probably not significant, based on the absence of cyclic GDGTs. While published reports find that Euryarchaeota halophiles grown in culture synthesize only archaeol, it has been suggested that the biphytanes (C40 chains) are biosynthesized via coupling of two geranyl–geranyl units using geranylgeranyl reductase, which produces the saturated biphytanyl chain (Chong, 2010 and references therein). If this is the case, it is noteworthy that geranylgeranyl reductase has thus far been identified in many methanogens (e.g. Anderson, 2009) and halophiles (e.g. Baliga et al., 2004; Bolhuis et al., 2006; Hartman et al., 2010). Additional unpublished genomes also provide preliminary genomic evidence for potential halophilic production of biphytanes (http://www.ncbi.nlm.nih.gov). Understanding all enzymatic steps in biphytane synthesis and cyclization is still lacking, however (Boucher et al., 2004; Lai et al., 2009). Enzymology and experimental testing of salinity–lipid relationships using enrichment mesocosms and isolated Archaea are key to further evaluation of the ACE salinity indicator and the presence of caldarchaeol in halophiles. Finally, the Themoplasmatales are also a potential source of the caldarchaeol. They are commonly detected in marine (e,g. Frigaard et al., 2006; Teske and Sorensen, 2008; Pi et al., 2009; Roussel et al., 2009) and hypersaline environments (Benlloch et al., 2002; Jahnke et al., 2008), although the only cultured representatives are acidophiles (e.g. Ferroplasma). Since the marine and hypersaline representatives remain uncultured, the lipid distributions have not been directly observed. However, the highest caldarchaeol concentration found in a study of Guerrero Negro hypersaline mats was at the same sediment depth as the highest proportion of Thermoplasmatales (Jahnke et al., 2008). Therefore, this group may be important in the distribution of archaeol and caldarchaeol in hypersaline sediments. Future work should focus on identifying and enriching Thermoplasmatales in hypersaline surface waters to determine if planktonic groups are also important. Discriminating between planktonic and subsurface archaeal communities is especially important because our lipid-based salinity estimates, as with other indices using lipids which are synthesized by both planktonic and sedimentary microbes (e.g.TEX86), assume planktonic archaeal lipids are the major contributors to the sedimentary ether isoprenoid lipid record. This implies that subsurface Archaea inputs, both during and after deposition, do not influence lipid relative abundances. The active debate on the role of intact polar lipids as markers of in situ microbial production (Lipp and Hinrichs, 2009) vs. preservation of plankton-derived lipids (Schouten et al., 2010) will further elucidate the degree to which subsurface Archaea impact paleorecords based on archaeal lipids. While it appears that metabolically active post-depositional subsurface Archaea have been found in sapropels (Coolen et al., 2002), we found no correlation between increase in ACE values and total organic carbon (TOC) where TOC data were available. More importantly, metabolic rates in most subsurface environments are slow and extant archaeal biomass contribution is low (D’Hondt et al., 2002; Schippers et al., 2005 Biddle et al., 2006). Nonetheless, since both archaeol and caldarchaeol may be synthesized by subsurface Archaea, care should be taken in applying ACE

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in environments with evidence for increased subsurface microbial biomass, such as areas of microbial methane cycling. 4.2. Preservation of the lipid–salinity relationship in sediments 4.2.1. Surface sediments ACE values based on archaeol and caldarchaeol in surface sediments generally compare well with measured SPM ACE values from overlying waters, and the differences shed light on the possible origins and bias in the distribution of archaeol and caldarchaeol (Table 1). In the Arabian Sea, Black Sea, Eq. Pacific and salt pans, the sediment ACE and SPM ACE values are well correlated. The ACE value for the sediment from the salt pan was greater than the surface water SPM value, but represents an average salinity over the course of a salt harvesting season. Low ACE values for the underlying sediment in Chincoteague Bay may result as water column Archaea bypass local sedimentation, entrained in the strong currents. The discrepancy between the sedimentary ACE and SPM ACE suggests coastal estuarine–marine environments, through the influences of terrestrial input, seasonal variation and dynamic sedimentation create inconsistent relationships between surface water and sedimentary lipids. 4.2.2. Lipid–salinity relationship in ancient applications Mineralogical, faunal and isotopic evidence are indicative of a diachronous onset of hypersalinity in the TV and SP sections (Bellanca et al., 2001). In both sections, evaporite mineral pseudomorphs (gypsum and celestite) are intermittently present. Foraminifera and calcareous nannoplankton gradually disappear and diatom diversity decreases sharply toward the top of the sections (Bellanca et al., 2001). In both sections, variation in ACE salinity calculations is consistent with expected values for the transition from marine to hypersaline conditions and track periods of evaporation and dilution recorded in the stable isotope composition of minerals (Bellanca et al., 2001). In the TV section, d18O values vary between +5.1‰ and +8.1‰ prior to deposition of laminar gypsum, which indicates the presence of an enriched evaporative brine. The increase in calculated salinity to 130 psu at 13.9 m tracks this period of d18O enrichment. In the SP section, several negative excursions in d18O values throughout the section are evidence for freshwater input (Bellanca et al., 2001). Specifically, d18O decreases (ca. 2‰) at 18.5 and 19.2 m, which Bellanca et al. (2001) interpret as an influx of continental water. The decreases in d18O values are accompanied by decreases in the lipid-based salinity calculations, although there is not a linear relationship between the ACE values and d18O values at specific depths. The d18O is measured at higher resolution than the lipid record and perhaps is also more sensitive to complex and rapid changes in evaporation–precipitation processes, more directly recording changes in water composition. Calculation of the oxygen isotope composition of water based on the oxygen isotopes of carbonate (Bellanca et al., 2001) using Erez and Luz (1983), and assuming an average annual temperature of 20 °C, the calculated salinity (Doose et al., 1999) for the TV section is consistently between 32 and 35 psu and 38–42 psu for SP. These values are lower than the ACE calculated salinity at the top of the sections, where evaporite minerals indicate the onset of hypersalinity. In contrast, lipid based salinity values are at lower resolution and are therefore biased against recording higher resolution variations such as annual evaporation–precipitation cycles. Lipid values may also be impacted by ecological hysteresis, indirectly recording salinity variation. The maximum ACE salinity values are 140 and 160 psu, again consistent with mineralogical and faunal evidence for increased salinity. Despite the limited stratigraphic resolution, these ACE values reveal two distinct patterns

of hypersalinity onset. In SP, there is a pulsed onset, characterized by an alternating period of marine and hypersaline conditions, which is supported by microfossil and isotope evidence. In TV, there is a rapid onset of hypersalinity consistent with the rapid deposition of laminar gypsum. Stromatolites, with isotopic evidence of anaerobic methane oxidation, were recently described in neighboring outcrops of the Caltanissetta Basin, with stromatolitic facies running from the top of the Tripoli Formation and into the Calcare di Base (Oliveri et al., 2010). Cyanobacterial DNA was also recently extracted and analyzed from Messinian gypsum crystals (Panieri et al., 2010). Both studies show the succession of adapted microbial populations within a persistent hypersaline environment. 4.3. Strength and limitations of ACE salinity index ACE values can be used to determine paleosalinity in the hypersaline range, but are not well calibrated for normal marine environments. Further calibration over a range of time periods and hydrographic regimes is obviously required. Analytically, archaeol detection by way of LC–MS requires improvement in resolution, sensitivity and reproducibility. The source of caldarchaeol in hypersaline salt pans also remains unclear. Allochthonous input of terrestrial lipids seems unlikely given the correlation between salinity and lipid distributions, and the lack of other GDGTs in the hypersaline ponds. Minor caldarchaeol production by halophiles is theoretically possible, but has never been directly observed. Thermoplasmatales are also a potential source, but water and sediment sources need to be deconvoluted. Furthermore, environments with anaerobic oxidation of methane also may produce both archaeol and caldarchaeol. Pancost et al. (2005) showed the presence of both compounds in carbonate crusts associated with methane seeps in the Gulf of Mexico. Blumenberg et al. (2004) observed variation in the ratio of phytane and biphytane lipids in the benthic mats associated with gas-seep carbonate chimneys in the Black Sea. Based on genomic analysis, Crenarchaeota appear to be extremely minor in the mats and GDGTs with 0, 1 and 2 rings, and diethers, and are thought to be synthesized by ANME Archaea. Therefore, these studies show that in environments with AOM communities, both archaeol and caldarchaeol may be derived from ANME bacteria, which may impact or bias salinity calculations. Therefore, care should be taken to recognize the potential for AOM when analyzing paleorecords, especially when using carbon isotopes to detect microbial update of 13C depleted biogenic methane. A combination of environmental genomic and lipid analyses, as well as incubation and culture experiments can also help elucidate sources of lipids. In industrial salt flats in Baja California (Guerrero Negro), Jahnke et al. (2008) studied lipid distributions combined with molecular ecology. The pond studied had a salinity of ca. 70 psu at the time of sampling. The relative distribution of phythanyl (diether fragments) and biphytanyl (tetraether fragments), led to a ratio of 132:1 in the surface sediments. The calculated phytanyl/phytanyl + biphytanyl  100 values range from 80–98, close to the maximum possible ACE value (100), and much higher than the values calculated from any sample in this study. From the equation established here, the salinity in the Guerrero Negro salterns would be calculated to be 262 psu, higher than the salinity in the highly managed water flow system (Des Marais, 1995). Differences in methodology may be responsible for the discrepancy; Jahnke et al. (2008) used GC–MS analysis of hydrocarbon moieties after ether cleavage to measure lipid abundances. ACE has the important benefit of preferential preservation under conditions where other potential proxies are absent or altered.

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Few macrofauna are available to indicate high salinity and Archaea and their lipid biomarkers tend to endure in basins when other biological indicators of salinity are absent, such as during periods of anoxia or calcium carbonate dissolution (Schouten et al., 2002). The use of hydrogen isotope compositions of lipids in hypersaline environments may also provide an additional complementary method for calculating salinity (e.g. Andersen et al., 2001; Rohling, 2007; van der Meer et al., 2007). Additionally, especially at lower salinity, the strength of ACE may be to establish ranges for salinity, rather than specific salinity values. Given the large uncertainties, and until further calibrations are made, one approach might be to use the following scale for establishing salinity ranges: (i) ACE < 1 = <25 psu. (ii) ACE < 10 = <50 psu. (iii) ACE > 40 = >75 psu. In the future, ACE values can be more finely calibrated and used to calculate absolute salinity values, thereby providing more nuanced understanding of salinity ranges within what that broadly labeled as hypersaline. As we have shown for the Messinian, the ACE index demonstrates expected differences in the onset of hypersalinity in two syndepostional basins. Understanding the timing and amplitude of progressive hypersalinity, and return to marine conditions, is relevant for critical intervals in the Earth’s history, such as Proterozoic (and perhaps Archaean) evolution, the end-Permian and the Messinian Salinity Crisis. 5. Conclusions The relative abundance of archaeol to caldarchaeol (simplified to the acronym ACE) in suspended particles is positively correlated with salinity across an extreme range from marine to hypersaline waters. The relationship between salinity and lipid distribution probably reflects ecological changes in the Archaea community and resulting lipid production. In surface sediments, the salinity correlation affords appropriate salinity calculations for brackish, marine and hypersaline sites (Black Sea, Eq. Pacific, Infersa salt ponds, Sicily) which are not influenced directly by terrestrial input or seasonal variation. In ancient sedimentary OM from a marine-tohypersaline transition, calculated paleosalinity variation based on archaeal lipids is consistent with values expected from mineralogy, macrofaunal changes and oxygen isotopes. ACE values have the potential to constrain absolute salinity, ultimately providing insights into the climatically sensitive properties of hypersaline basins. Acknowledgements E.C. Hopmans, S. Schouten and J.S. Sinninghe Damsté generously provided initial HPLC-MS training at NIOZ. Infersa Saline, Marsala, Italy and the A. D’Ali Staiti family kindly provided access to salt pan sites where R.L. Folk (University of Texas) served as translator and alkalinity titrator. The Marine Science Consortium (Wallops Island, VA) provided access to Chincoteague Bay sites. J. Geagan and C. Lernihan assisted in the field. S. Wakeham provided many marine SPM samples and M. Conte allowed us to join the scientific party aboard the R/V Weatherbird II. We also thank the R/V Weatherbird II crew. A. Caruso (University of Pisa) provided Messinian samples and directions to sites. M. Arthur and R. Summons gave insightful criticisms; L. Jahnke and an anonymous reviewer also provided comments for considerable improvements to the manuscript. An AAPG Grant-in-Aid, NSF-IGERT DGE-9972759 and NSF OCE-327377 funded this research. Associate editor—R.D. Pancost

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