Stable carbon isotope patterns of marine biomarker lipids in the Arctic Ocean during Eocene Thermal Maximum 2


  • Petra L. Schoon,

    1. Department of Marine Organic Biogeochemistry, NIOZ Royal Netherlands Institute for Sea Research, Den Burg, Netherlands
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  • Appy Sluijs,

    1. Biomarine Sciences, Laboratory of Palaeobotany and Palynology, Institute of Environmental Biology, Faculty of Science, Utrecht University, Utrecht, Netherlands
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  • Jaap S. Sinninghe Damsté,

    1. Department of Marine Organic Biogeochemistry, NIOZ Royal Netherlands Institute for Sea Research, Den Burg, Netherlands
    2. Department of Earth Sciences–Geochemistry, Faculty of Geosciences, Utrecht University, Utrecht, Netherlands
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  • Stefan Schouten

    1. Department of Marine Organic Biogeochemistry, NIOZ Royal Netherlands Institute for Sea Research, Den Burg, Netherlands
    2. Department of Earth Sciences–Geochemistry, Faculty of Geosciences, Utrecht University, Utrecht, Netherlands
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[1] The middle Paleocene through early Eocene long-term gradual warming was superimposed by several transient warming events, such as the Paleocene-Eocene Thermal Maximum (PETM) and Eocene Thermal Maximum 2 (ETM2). Both events show evidence for extreme global warming associated with a major injection of carbon into the ocean-atmosphere system, but the mechanisms of carbon injection and many aspects of the environmental response are still poorly understood. In this study, we analyzed the concentration and stable carbon isotopic (δ13C) composition of several sulfur-bound biomarkers derived from marine photoautotrophs, deposited in the Arctic Ocean at ∼85°N, during ETM2. The presence of sulfur-bound biomarkers across this event points toward high primary productivity and anoxic bottom water conditions. The previously reported presence of isorenieratene derivatives indicates euxinic conditions in the photic zone, likely caused by a combination of enhanced primary productivity and salinity stratification. The negative carbon isotope excursion measured at the onset of ETM2 for several biomarkers, ranges between 3‰ and 4.5‰, much larger than the ∼1.4‰ recorded in marine carbonates elsewhere, suggesting substantial enhanced isotopic fractionation by the primary producers likely due to a significant rise in pCO2. In the absence of biogenic carbonates in the ETM2 section of our core we use coeval planktonic δ13C from elsewhere to estimate surface water δ13C in the Arctic Ocean and then apply the relation between isotopic fractionation and pCO2, originally calibrated for haptophyte alkenones, to three selected organic biomarkers (i.e., S-bound phytane, C35 hopane, and a C25 highly branched isoprenoid). This yields pCO2 values potentially in the range of four times preindustrial levels. However, these estimates are uncertain because of a lack of knowledge on the importance of pCO2 on photosynthetic isotopic fractionation.

1. Introduction

[2] One of the most prominent features of Cenozoic climate is a global warming trend that started in the mid-Paleocene (∼59 Ma) and culminated during the Early Eocene Climatic Optimum (EECO; 52–50 Ma). During this time, several transient and geologically rapid episodes of extreme warming, or ‘hyperthermals’, occurred [e.g., Zachos et al., 2008; Lourens et al., 2005]. These hyperthermals are characterized by a pronounced negative carbon isotope excursion (CIE) recorded in both organic and inorganic carbon reservoirs, and widespread, though variable, dissolution of deep sea carbonates [Lourens et al., 2005; Sluijs et al., 2007; Stap et al., 2010; Leon-Rodriguez and Dickens, 2010]. These negative CIEs are generally thought to reflect the release of large amounts of 13C-depleted carbon into the exogenic carbon pool [Dickens, 2003]. The extensively studied Paleocene-Eocene Thermal Maximum (PETM, ∼56 Ma), was further characterized by ∼4–9°C warming of the continents and deep and surface ocean waters [e.g., Kennett and Stott, 1991; Tripati and Elderfield, 2005; Wing et al., 2005; Sluijs et al., 2006; Weijers et al., 2007]. Approximately two million years later, the PETM was followed by Eocene Thermal Maximum 2 (ETM2) and the H2 hyperthermal events, characterized by similar climatic and geochemical changes as the PETM but of smaller magnitude [Lourens et al., 2005; Nicolo et al., 2007; Sluijs et al., 2009; Stap et al., 2009, 2010].

[3] Critically, the magnitude of the CIE of the global exogenic carbon pool across the PETM remains contentious [Dickens, 2011]. Generally, calcium carbonate precipitated by benthic foraminifera in the deep ocean or outer shelf are considered to reliably reflect the global average magnitude of the CIE. However, the magnitude of the CIE may differ by up to 2‰ between such records [e.g., John et al., 2008; McCarren et al., 2008]. In part, this likely reflects regional or local climate-driven deviations in the stable carbon isotopic composition (δ13C) of dissolved inorganic carbon from mean ocean values, which may regionally increase or decrease the magnitude of the CIE. In addition, part of the marine CIE signal may regionally be truncated in the deep sea due to severe dissolution and temporal absence of the critical foraminifera species during the early stages of the event [e.g., Thomas et al., 2002; McCarren et al., 2008]. Finally, the magnitude of the CIE as recorded in foraminifera may have been dampened due to a decrease in seawater pH [Uchikawa and Zeebe, 2010]. The terrestrial CIE signal as recorded in paleosol carbonates is on average ∼1–2‰ larger than the marine signal [Bowen et al., 2001]. Although, in theory, the terrestrial carbonates should record the atmospheric CIE more directly, they may have been affected by diagenesis, and increased relative humidity and soil moisture [e.g., Bowen et al., 2004]. A large (4.5‰) CIE was also recorded in organic dinoflagellate cysts in two marginal marine sections [Sluijs et al., 2007], but, as yet, it remains uncertain if local factors other than the stable carbon isotopic composition (δ13C) of dissolved inorganic carbon influenced these records. Recent studies based on higher plant leaf wax n-alkanes [Handley et al., 2008; Pagani et al., 2006b; Smith et al., 2007] suggest a large magnitude of the PETM-CIE. However, biomarker analysis showed that angiosperms and gymnosperms have a different response to the environmental changes that took place during the PETM, resulting in different isotopic fractionation, causing an overestimation of the CIE [Schouten et al., 2007]. The large CIE signal of ∼6‰ generally recorded in terrestrial n-alkanes can therefore be explained by a shift in vegetation patterns from gymnosperm dominated to angiosperm dominated [Schouten et al., 2007; Smith et al., 2007]. Indeed, a recent tropical n-alkane record that should not be affected by such biases suggests a magnitude closer to 3‰ [Jaramillo et al., 2010].

[4] Molecular isotopic investigations on aquatic biomarkers have been limited to the δ13C record of the C17n-alkanes, possibly derived from algae and photosynthetic bacteria, which showed a lower CIE (∼3.5‰) compared to that of the terrestrial n-alkanes (5–6‰) [Pagani et al., 2006b]. However, it was suggested that the CIE recorded in the n-C17 alkanes was affected by increased paleoproductivity [Pagani et al., 2006b]. The isotopic response of marine primary producers during the PETM remains, therefore, poorly constrained.

[5] In contrast to the PETM, δ13C records of the CIE across ETM2 are relatively sparse [Lourens et al., 2005; Nicolo et al., 2007; Sluijs et al., 2009; Stap et al., 2010; Leon-Rodriguez and Dickens, 2010]. At Walvis Ridge, the magnitudes of warming (∼3°C), carbonate dissolution and the CIE in benthic foraminifera (∼1.4‰) are smaller than those at the PETM [Lourens et al., 2005; Stap et al., 2009, 2010]. ETM2 has recently been recognized in sediments deposited in the Central Arctic Ocean [Sluijs et al., 2009; Stein et al., 2006]. In a recent study, Sluijs et al. [2009] found cysts of freshwater tolerant dinoflagellate species to dominate assemblages during ETM2, suggesting a freshening, stratification, and eutrophication of the Arctic Ocean surface waters. Bottom water anoxia was inferred from the presence of laminated sediments and the absence of organic linings of benthic foraminifera [Sluijs et al., 2009]. Furthermore, at some occasions anoxic conditions even reached into the photic zone, based on the presence of isorenieratene derivatives. The sea surface temperature proxy TEX′86 [Sluijs et al., 2006] indicated that Arctic Ocean surface waters warmed by ∼4°C during ETM2 [Sluijs et al., 2009] though these estimates have some uncertainties (see detailed discussion in the Supplementary of Sluijs et al. [2009]). In addition, the presence of palm pollen in the interval of peak warmth implies that the mean temperature of the coldest month was above 8°C, constraining the lower temperature limit of the Arctic region during this Eocene hyperthermal event. This minimum temperature estimate is inferred from the habitats of modern biota. Paleobotanical inspection suggests that the stem structures of Paleogene palms is very similar to modern relatives which renders it highly unlikely that the palms were more resilient than at present [e.g., Royer et al., 2002; Greenwood and Wing, 1995]. The CIE in total organic carbon (TOC) is ∼3.5‰, [Sluijs et al., 2009], much larger than recorded in carbonates deposited elsewhere [Cramer et al., 2003; Lourens et al., 2005; Nicolo et al., 2007; Stap et al., 2009]. However, this bulk organic carbon isotope record may have been biased due to changes in the source (i.e., terrestrial versus marine) of the bulk organic carbon.

[6] To investigate the response of marine organisms across ETM2, we analyzed the concentrations and carbon isotopic composition of sulfur-bound biomarkers derived from marine phytoplankton in the Arctic Ocean record. Furthermore, we made a first attempt to roughly estimate changes in pCO2 across ETM2, using reconstructed carbon isotope fractionations of three independent groups of marine microorganisms. Such pCO2 estimates would considerably improve the insight in feedback mechanisms and climate sensitivity during past episodes of abrupt warming.

2. Methods and Materials

2.1. Sample and Site Description

[7] In 2004, Integrated Ocean Drilling Program (IODP) Expedition 302, also known as the Arctic Coring Expedition (ACEX), recovered lengthy portions of a 428 m marginal marine sedimentary sequence, at the crest of the Lomonosov Ridge in the Central Arctic Ocean (∼85°N paleolatitude) (Figure 1) [O'Regan et al., 2008]. Uppermost Paleocene and lower Eocene sediments deposited between 56 and 50 Ma consist of siliciclastic mudstones, barren of siliceous and calcium carbonate microfossils, but containing ample immature organic matter with a TOC content of up to 8% [Stein et al., 2006; O'Regan et al., 2008]. As suggested by the regular occurrence of dark laminated silty clays [O'Regan et al., 2008], the high content of total sulfur [Ogawa et al., 2009], the general absence of remains of benthic organisms [O'Regan et al., 2008; Sluijs et al., 2006, 2008], and trace metal information [Sluijs et al., 2008], Arctic bottom waters were low in oxygen content throughout the studied interval covering ETM2 [Sluijs et al., 2009], creating optimal conditions for biomarker preservation.

Figure 1.

Paleogeographical map of the Late Paleocene–Early Eocene Central Arctic Basin showing the position of IODP Hole 302-4A (modified from Sluijs et al. [2009]).

[8] We studied the sediments from before to after the carbon isotope excursion (CIE) associated with ETM2, which are located ∼20 m above the PETM. We used the same samples of Sluijs et al. [2009]. The identification of the ETM2 interval is based on the presence of the dinoflagellates Cerodinium wardenese and Hystrichosphaeridium tubiferum [Sluijs et al., 2008]. The onset of ETM2 is placed at ∼368.9 m composite depth below seafloor (mcd) according to the δ13C composition of TOC [Sluijs et al., 2009].

2.2. Biomarker Analysis

[9] Powdered and freeze-dried sediments (∼5 g dry mass) were extracted with a Dionex Accelerated Solvent Extractor using a 9:1 (v:v) mixture of dichloromethane (DCM) and methanol (MeOH). An aliquot of the total extract was desulfurized to release sulfur-bound hydrocarbons using Raney Nickel, as previously described by Sinninghe Damsté et al. [1988]. Prior to desulfurization an internal standard [2,3-dimethyl-5-(1,1-d2-hexadecyl)thiophene] was added to the total extract aliquots for quantitative analyses. Subsequently, the desulfurized total extracts were separated into polar and apolar fractions using a small column with activated alumina using hexane/DCM (9:1;v/v) and MeOH/DCM (1:1;v/v) as eluents, respectively. The apolar desulfurized fractions containing the released hydrocarbons, were hydrogenated using PtO2/H2 and analyzed by gas chromatography (GC) and GC/mass spectrometry (MS). GC analyses were performed using a Hewlett-Packard 6890 instrument equipped with a flame ionization detector (FID), a Flame Photometric Detector (FPD), and an on-column injector. A fused silica capillary column (25 m × 0.32 mm) coated with CP-Sil 5 (film thickness 0.12 μm) was used with helium as carrier gas. The oven was programmed at a starting (injection) temperature of 70°C, which rose to 130°C at 20°C/min and then to 320°C at 4°C/min, at which it was maintained for 20 min. GC/MS analysis was done using a Thermofinnigan TRACE gas chromatograph using similar GC conditions as described above. The gas chromatograph was coupled with a Thermofinnigan DSQ quadrupole mass spectrometer with ionization energy of 70 eV and fractions were analyzed in full scan mode with a mass range of m/z 50–800 at three scans per second.

[10] To prevent coelution, n-alkanes were removed from the apolar fraction using a small column containing silicalite and cyclohexane as eluent [West et al., 1990], before biomarker δ13C analyses. The samples were analyzed on a Finnigan Delta V isotope ratio monitoring mass spectrometer coupled to an Agilent 6890 GC. Samples, dissolved in n-hexane, were analyzed using GC under conditions as described above. All carbon isotope compositions for the individual components are reported relative to the Vienna Pee Dee Belemnite (VDPB) standard and are average values of at least two runs.

3. Results

3.1. Biomarker COMPOSITION

[11] Analysis of selected apolar fractions of sediments in the studied ETM2 interval showed a relatively high abundance of organic sulfur compounds (OSCs), such as C25 HBI thiolanes [Kohnen et al., 1990] and a C35 hopanoid thiophene [Valisolalao et al., 1984]. The presence of these low molecular weight organic sulfur compounds suggests that sulfur has reacted with functionalized labile lipids and likely indicates the presence of more complex, higher molecular weight, organic sulfur compounds [Sinninghe Damsté and de Leeuw, 1990], which can potentially bias the distribution of biomarkers in apolar fractions [Kohnen et al., 1991]. Therefore, to release all S-bound carbon skeletons we desulfurized the total extracts using Raney Nickel [Sinninghe Damsté et al., 1988]. Apolar fractions of the desulfurized extracts contain mostly S-bound hydrocarbons, including 5α-C27–C29 steranes, C30–C35 hopanes, a C25 HBI and isorenieratane, predominantly with the 17β,21β(H)configuration, and some free hydrocarbons, i.e., n-alkanes with a slight odd-over-even carbon number predominance (see Figure 2 for a typical gas chromatogram of one of the samples). We focused on five biomarkers for quantification and isotopic study (Figures 2 and 3). S-bound phytane is an early diagenetic product of S-bound phytol [Brassell et al., 1986]. Whereas phytol is part of the chlorophyll a molecule, and consequently characteristic for all primary producers using photosynthesis, including cyanobacteria. It is unlikely that this sulfur-bound phytane derives from terrestrial chlorophyll as sulfur-incorporation occurs during early diagenesis, i.e., almost immediately after burial [e.g., Sinninghe Damsté and de Leeuw, 1990]. Furthermore, S-bound phytane has a different isotopic composition than that of ‘free’ phytane showing its different origin [Kohnen et al., 1992; Koopmans et al., 1999]. S-bound C25 HBI is derived from unsaturated C25 HBIs, which are synthesized by diatoms [Volkman et al., 1994] and serves as a biomarker for four specific diatom genera (Rhizosolenia, Haslea, Navicula, and Pleurosigma) [Sinninghe Damsté et al., 2004a, and references therein]. S-bound C31 17β,21β(H)-homohopane and S-bound C35 17β,21β(H)-pentakishomohopane derive from derivatives of the membrane lipid bacteriohopanepolyol. These compounds are produced by a large number of aerobic bacteria, including cyanobacteria [Rohmer et al., 1992; Talbot et al., 2008, and references therein], but have also been found in some strictly anaerobic bacterial groups [Fischer et al., 2005; Sinninghe Damsté et al., 2004b]. The source of these compounds is therefore uncertain. We did not detect any 2-methyl hopanoids, which are considered to be specific for most, although not all, cyanobacteria [Summons et al., 1999] and therefore a cyanobacterial origin for S-bound C35 hopane cannot be confirmed. However, it is often presumed, based on isotopic studies, that C35 hopane in marine sediments is mainly derived from cyanobacteria [Schoell et al., 1994; Sinninghe Damsté et al., 2008]. Previously, we reported the presence of low amounts of S-bound isorenieratane in sediments between 368.9 and 367.9 mcd [Sluijs et al., 2009]. The precursor of S-bound isorenieratane is the diaromatic carotenoid isorenieratene. This pigment is produced by the brown strain of green sulfur bacteria, which are anaerobic photoautotrophs that thrive under euxinic (high free sulfide and low oxygen) conditions within the photic zone [Sinninghe Damsté et al., 1993]. In summary, it is likely that the selected biomarkers, except for S-bound isorenieratane, are all derived from marine primary producers, particularly as they are sulfur-bound and thus derived from labile precursors. Hence, they can provide insight into the response of these groups of organisms during ETM2 in the Arctic Ocean.

Figure 2.

GC chromatogram of the desulfurized apolar fraction of sample 302-4A-27X-1, 118–120. Indicated are the n-alkanes (circles), C27–C29 steranes (triangles), and C30–C35 hopanes (diamonds). Chemical structures of the S-bound biomarkers of which the concentrations and δ13C values were measured are indicated at the corresponding peaks.

Figure 3.

(a) Concentration profiles and (b) stable carbon isotope profiles of TOC [Sluijs et al., 2009] and the specific S-bound biomarkers phytane, C25 HBI, C31 hopane, C35 hopane, and isorenieratane. The concentrations are denoted in μg/g C and δ13C values are in ‰ VPDB.

3.2. Biomarker Abundance

[12] In the interval just below the CIE, concentrations of phytane and C25 HBI, both indicators for marine phytoplankton, are low (<15 μg/g TOC; Table 1 and Figure 3a). In contrast, both bacterial biomarkers, the C31 and C35 hopane, are relatively abundant (>45 μg/g TOC), while isorenieratane is below detection limit. Across the onset of the CIE, all biomarker concentrations remain relatively low, except for a short-lived increase in C31 hopane concentrations (up to ∼170 μg/g TOC) at ∼368.88 mcd. This coincides with the first detection of isorenieratane (∼4 μg/g TOC). Immediately after the peak of the CIE, at ∼368.72 mcd, phytane, C35 hopane and the C25 HBI concentrations sharply increase, with peak values of ∼50, ∼100, and ∼120 μg/g TOC, respectively. Isorenieratane is detected between 368.74 and 368.48 mcd, with peak concentrations of ∼15 μg/g C at 368.62 mcd [Sluijs et al., 2009]. Concentrations of phytane, the C25 HBI and C35 hopane are relatively high during this interval, but are relatively low at ∼368.62 mcd where the isorenieratane concentration reaches its maximum. The C31 hopane abundance remains relatively constant across the interval of detectable isorenieratane. Above 368.48 mcd, all biomarker concentrations return toward the “background” pre-ETM2 values. However, elevated isorenieratane, C25 HBI and C35 hopane concentrations reoccur between 367.99 and 367.90 mcd. This interval also exhibits a negative excursion in δ13CTOC (Figure 3b) and was therefore suggested by Sluijs et al. [2009] as a potential candidate for the H2 event [Cramer et al., 2003], which has recently been shown to also reflect a hyperthermal [Stap et al., 2010].

Table 1. Relative Abundances of TOC and S-Bound Biomarkers
SampleDepth (mcd)TOCa (%)PhytaneC25 HBI (μg/g C)C31ββ Hopane (μg/g C)C35ββ Hopane (μg/g C)Isorenieratane (μg/g C)

3.3. Compound-Specific Stable Carbon Isotope Analysis

[13] Stable carbon isotope analyses were performed, where possible, on phytane and C25 HBI as biomarkers for marine photosynthetic algae, and on C31 hopane and C35 hopane as biomarkers for (cyano)bacteria (Figure 3b and Table 2). We were able to determine the δ13C composition of isorenieratane for the sediments at 368.88 and 368.72–368.54 mcd (Table 2). Isorenieratane δ13C values are 11–14‰ enriched relative to phytane in the same samples. Green sulfur bacteria use the reversed tricarboxylic acid cycle that discriminates much less against 13C than the Calvin cycle, which is used by most photoautotrophic organisms [Quandt et al., 1977]. An enrichment of this magnitude for isorenieratane can therefore be expected and is consistent with previous observations [Koopmans et al., 1996; van der Meer et al., 1998].

Table 2. Stable Carbon Isotopic Composition (in ‰ VPDB) and Standard Deviation of TOC and S-Bound Biomarkersa
SampleDepth (mcd)δ13C (‰)
TOCPhytaneC25 HBIC31ββ HopaneC35ββ HopaneIsorenieratane
  • a

    Stable carbon isotopic composition is in ‰ VPDB.

302-4-27X1-40-41367.80−28.1−33.3 ± 0.1−34.9 ± 0.0−34.4 ± 0.2−31.7 ± 0.1 
302-4-27X1-50-51367.90−28.0−32.9−34.9−34.2 ± 0.5−31.6 ± 0.2 
302-4-27X1-55-57367.95−29.6−32.6 ± 0.1−34.9 ± 0.2−34.1 ± 0.3−32.0 ± 0.6 
302-4-27X1-59-61367.99−29.1−33.5 ± 0.1−33.5 ± 0.1−33.8 ± 0.4−32.4 ± 0.3 
302-4-27X1-64-66368.04−27.2−33.8 ± 0.1−33.7 ± 0.1−34.0 ± 0.3−32.6 ± 0.2 
302-4-27X1-68-70368.08−27.7−33.8 ± 0.0−35.9−33.5 ± 0.8−32.0 ± 0.5 
302-4-27X1-72-74368.12−27.7−33.3−34.3 ± 0.3−34.8 ± 0.5−32.4 ± 0.0 
302-4-27X1-80-82368.20−27.8−33.4 ± 0.5−36.3 ± 0.3−34.7 ± 0.1−32.9 ± 0.3 
302-4-27X1-83-85368.23−27.9−34.7 ± 0.3−35.7 ± 0.2−35.2 ± 0.2−33.1 ± 0.1 
302-4-27X1-88-90368.28−28.6−35.8 ± 0.1−36.6 ± 0.0−34.9 ± 0.0−32.8 ± 0.1 
302-4-27X1-94-96368.34−28.9−35.7 ± 0.1−37.0 ± 0.4−35.1 ± 0.2−32.7 ± 0.3 
302-4-27X1-100-102368.40−28.8−35.6−35.8 ± 0.0−35.2−33.3 ± 0.4 
302-4-27X1-104-106368.44−29.4−35.5 ± 0.1−36.6 ± 0.1−35.1 ± 0.3−33.4 ± 0.2 
302-4-27X1-108-110368.48−29.1−34.2 ± 0.3−34.7 ± 0.4−34.5 ± 0.1−32.8 ± 0.2 
302-4-27X1-114-116368.54−29.3−33.9 ± 0.1−34.6 ± 0.1−34.4 ± 0.2−32.1 ± 0.3−22.1 ± 0.5
302-4-27X1-118-120368.58−29.3−34.6 ± 0.1−33.9 ± 1.2−34.6 ± 0.3−32.6 ± 0.3−21.4 ± 1.2
302-4-27X1-122-124368.62−29.8−34.9 ± 0.0−35.9 ± 0.0−35.5 ± 0.1−32.2 ± 0.0−21.6 ± 0.3
302-4-27X1-132-134368.72−30.8−37.2 ± 0.1−37.7 ± 0.0−36.7 ± 0.3−35.0 ± 0.1−26.3
302-4-27X1-134-136368.74−30.8−37.0 ± 0.1−37.7 ± 0.1−37.0 ± 0.3−35.5 ± 0.2 
302-4-27X1-139-141368.79−31.2−37.1 ± 0.3−36.3 ± 0.1−34.8 ± 0.1−35.0 ± 0.0 
302-4-27X1-144-146368.84−29.6−35.7 ± 1.0−35.0 ± 0.6−35.7 ± 0.3−34.8 ± 0.3 
302-4-27X1-148-150368.88−28.5−35.7 ± 0.4−34.7 ± 0.3−35.5 ± 0.1−33.8 ± 0.2−21.4 ± 0.1
302-4-27X2-0-2368.90−27.4−34.7 ± 0.0−34.6 ± 0.4−32.3 ± 0.1−31.6 ± 0.1 
302-4-27X2-4-6368.94−26.7−33.0 ± 0.7−34.2−32.4−32.3 ± 0.1 
302-4-27X2-12-14369.00−27.5−32.6 ± 0.5−33.8 ± 0.4−32.5 ± 0.2−31.2 ± 0.1 
302-4-27X2-14-16369.04−27.9−34.6 ± 0.2−33.7 ± 0.1−32.5 ± 0.1−31.3 ± 0.1 
302-4-27X2-19-21369.09−27.0−34.5−32.5−32.6 ± 0.4−31.7 ± 0.6 
302-4-27X2-23-25369.13−26.4−34.4 ± 0.2−33.7−33.8 ± 0.2−31.9 ± 0.2 
302-4-27X2-28-30369.18−27.8−34.5 ± 0.8−33.6 ± 0.5−33.5 ± 0.3−31.8 ± 0.1 
302-4-27X2-31-33369.21−27.5−32.7 ± 0.3−33.3 ± 0.1−32.8 ± 0.1−31.8 ± 0.1 
302-4-27X2-44-45369.34−27.3−33.6−32.0 ± 0.2−32.3 ± 0.9−31.8 ± 0.2 
302-4-27X2-50-51369.40−27.7−34.4 ± 0.1−32.8 ± 0.4−33.3 ± 0.3−31.3 ± 0.3 
302-4-27X2-60-61369.50−27.6−34.5 ± 0.6−33.9 ± 0.3−33.6 ± 0.0−31.2 ± 0.1 
302-4-27X2-70-72369.60−27.5 −33.2 ± 0.3−32.8 ± 0.4−30.5 ± 0.3 

[14] Prior to the CIE of ETM2, the carbon isotope values are relatively stable, i.e., −27.3 ± 0.6‰ for TOC, −33.9 ± 0.8‰ for phytane, −33.2 ± 0.7‰ for C25 HBI, −32.9 ± 0.5‰ for C31 hopane and −31.5 ± 0.5‰ for C35 hopane. The drop in δ13C of the analyzed specific biomarkers is essentially synchronous with the onset of the CIE in TOC [Sluijs et al., 2009], confirming the initiation of the CIE at ∼368.9 mcd. This drop is ∼3.2 and ∼4.5‰ for the algal biomarkers phytane and C25 HBI respectively, and ∼4.1‰ for both the C31 and C35 hopane. Except for phytane, the magnitudes of the shifts are slightly higher than the ∼3.5‰ shift in TOC.

[15] Between 368.72 and 368.23 mcd, the δ13CTOC record shows a gradual recovery toward ‘background’ pre-ETM2 values. Interestingly, the biomarker δ13C records show a more complex pattern (Figure 3b). An initial increase in δ13C values at ∼368.7 mcd, is followed by a second drop in δ13C between 368.48 and 368.23 mcd for phytane and C25 HBI. At 368.2 mcd all biomarkers have returned to their ‘background’, i.e., pre-ETM2 values. The potential presence of H2, based on the δ13CTOC record, is not apparent in the δ13C records of any of the analyzed biomarkers.

4. Discussion

4.1. Climatic and Environmental Changes Across ETM2 in the Arctic Ocean

[16] Prior to the onset of ETM2, both the biomarker concentrations and δ13C values show only minor variations, suggesting that environmental conditions were relatively stable (Figures 3a and 3b). Furthermore, no isorenieratane is detected in these sediments implying that the water column was not euxinic within the photic zone. This is also supported by relatively stable assemblages of typical open marine dinoflagellate cysts in this interval [Sluijs et al., 2009]. Relatively high TOC concentrations and the presence of “sulfur-bound” organic molecules in these sediments points toward a relatively productive paleoenvironment and low bottom water oxygen concentrations, which is in agreement with previous observations [Sluijs et al., 2008; Stein et al., 2006].

[17] The synchronous drop in δ13C at ∼368.9 mcd of both the specific biomarkers and TOC confirms that the CIE in TOC is not caused by changes in the composition of the bulk organic matter, but is linked to the injection of 13C-depleted carbon into the global exogenic carbon pool. During the recovery of ETM2, the δ13C of the biomarkers no longer track the δ13CTOC profile. The δ13CTOC record shows a smooth return to background δ13C values from 368.8 mcd, while the δ13C profiles of the biomarkers abruptly move toward more positive values at 368.6 mcd (Figure 3b). Additionally, directly after the CIE, at ∼368.7 mcd, there is a sharp increase in concentrations of phytane, C25 HBI and C35 hopane, which is followed by the development of photic zone euxinia (PZE) as indicated by the presence of isorenieratene derivatives. Possibly, enhanced productivity contributed to the development of PZE conditions in this interval, as was suggested for ETM2 and the PETM in the Arctic Ocean [Sluijs et al., 2006, 2009; Stein et al., 2006]. The increase in biomarker concentrations may also be explained by an increase in export production. However, Knies et al. [2008] investigated the response of marine productivity to variations in nutrient supply to the Cenozoic Arctic Ocean using nitrogen isotopes. For ETM2 they found evidence for an increase in primary production rates even after correcting for the higher burial efficiency caused by the euxinic conditions. Furthermore, abundances of the freshwater tolerant dinoflagellate species that peak synchronously with isorenieratane concentrations are also regarded as indicators for nutrient-rich conditions [Sluijs et al., 2005, 2009]. Although the timing with these dinoflagellate peaks is not perfectly synchronous, an increase in primary productivity could explain the increase in biomarker concentrations and the positive isotope shift in the specific biomarkers at 368.6 mcd, as an increase in primary productivity can lead to increased growth rates and decreased isotopic fractionation [Jasper and Hayes, 1990; Laws et al., 1995; Bidigare et al., 1997; Popp et al., 1998a, 1998b]. Therefore, although the lipids obviously had to be exported from the surface ocean to settle on the seafloor, the increase in concentrations in our view was at least partially related to increased productivity. This would imply that during this interval regional effects control the biomarker records, whereas TOC in this case more accurately tracks the δ13C evolution of the exogenic carbon pool.

[18] At ∼368.48 mcd, biomarker concentrations decrease and isorenieratane is below detection limit (Figure 3a), suggesting that the PZE conditions ended. Subsequently, all biomarker isotope values return to ‘background’ pre-ETM2 values and continue to track the δ13CTOC signal (Figure 3b).

4.2. H2 Event

[19] At ∼368.0 mcd the TOC record exhibits a second negative CIE of ∼2‰ (Figure 3b). This interval was previously interpreted to possibly reflect the H2 event, although a potential hiatus and the absence of a biostratigraphic framework with sufficient detail complicates exact identification [Sluijs et al., 2009]. Indeed, the presence of isorenieratane coincident with the dominance of low-salinity-tolerant dinoflagellate species [Sluijs et al., 2009], points to similar conditions as for ETM2. Remarkably, however, there is no negative carbon isotope shift in the biomarker δ13C records. There are two possible explanations for this apparent discrepancy. (1) The negative δ13C shift in TOC records an isotope excursion of the global exogenic carbon pool, but is obscured in the δ13C records of the biomarkers because of an increase in productivity, although this likely should have affected δ13CTOC as well. (2) The shift in the δ13CTOC record is not recording a CIE but is caused by a change in source material transported toward the Arctic Basin. None of these explanations can be completely excluded and, thus, the nature of this interval cannot be further elucidated based on the δ13C profiles of these marine biomarkers.

4.3. Estimating Isotopic Fractionation Across ETM2

[20] Based on the measured stable isotopic composition of S-bound phytane, C25HBI and C35 hopane, we estimated the average carbon isotopic fractionation of photoautotrophs, and changes therein. Averaged δ13C values were calculated for three time intervals: the pre-ETM2 interval (369.60–368.94 mcd), the CIE of ETM2 (368.84–368.72 mcd), and the post-ETM2 interval (368.20–368.04 mcd). Average biomarker δ13C values for these three periods were used to estimate the isotopic fractionation (ɛp):

display math

where δp is the δ13C value of the total organic carbon of the organism and δd is the δ13C value of the carbon substrate. To obtain δp, a correction must be made for the isotopic offset between the biomarker lipid and cell biomass. Schouten et al. [1998] and Oakes et al. [2005] reported, based on culture experiments and literature study of a range of different algae, that phytol is ∼6‰ depleted relative to the total algal biomass. For C25 HBIs a depletion of 6.6‰ relative to biomass was reported by Schouten et al. [1998] for the diatom Rhizosolenia setigera, whereas Massé et al. [2004] found similar carbon isotopic compositions of the C25 HBIs and phytol in Haslea ostrearia. This suggests an isotopic offset of ca. 6‰ for both phytane and C25 HBI. Results from culture experiments of the cyanobacterium species Synechocystis revealed an isotopic offset of 8.4‰ for bishomohopanol [Sakata et al., 1997].

[21] Values for δd can be obtained from the carbonate shells of planktonic foraminifera using the following equation:

display math

The δ13C of planktonic foraminifera (δ13Cpf) represents the δ13C composition of the primary carbon in CaCO3. The term between brackets describes the isotopic effect associated with the equilibrium exchange reaction between CO2aq and HCO3 as reported by Mook et al. [1974], which only depends on temperature (T in degrees Kelvin).

[22] Unfortunately, foraminiferal carbonate is absent in ACEX sediments [Sluijs et al., 2008, 2009]. Instead, we used the δ13C values of the surface-dwelling genus Acarinina reported for ETM2 at Walvis Ridge [Lourens et al., 2005; Stap et al., 2010]. Although this induces one factor of uncertainty, the δ13Cpf of ∼2‰ for the period prior to ETM2 compares quite well with those of stacked carbonate isotope records, as well as with modeling studies for the Early Eocene [Hayes, 1999; Berner, 2006; Berner and Kothavala, 2001], suggesting that this assumption is reasonable. We do not believe that in the semi-enclosed Arctic Basin additional effects, such as the input of recycled CO2 from anoxic deep waters play a large role. Van Breugel et al. [2006] demonstrated that in an anoxic marine system the effect of recycling of respired CO2 on the δ13C of phytoplankton lipids is negligible. Sea surface temperatures (SSTs) used in equation (2) were obtained from the oxygen isotopes of the same foraminiferal records from Walvis Ridge and a TEX86 measurement during ETM2 [Stap et al., 2010].

[23] The calculated ɛp values for the preexcursion interval show remarkably high carbon isotope fractionation factors of ca. 21–22‰ and ca. 14.5‰ for marine algae and (cyano)bacteria, respectively (Table 3). The lower value determined for (cyano)bacteria is consistent with the smaller carbon isotopic fractionation by cyanobacteria in comparison to algae [Hayes, 2001; Popp et al., 1998b]. During ETM2, ɛp values increase even further by 1–2‰. For all three biomarkers this results in ɛp values that lie close to the maximum fractionation of photoautotrophic organisms, i.e., 25–28‰ for the Rubisco enzyme of autotrophic eukaryotes [Bidigare et al., 1997; Goericke et al., 1994; Popp et al., 1998b] and 16–22‰ for autotrophic cyanobacteria [Sakata et al., 1997, and references therein].

Table 3. Estimations for pCO2 Based on the δ13C Composition of S-Bound Phytane, C25 HBI, and C35 Hopane
Biomarkerδ13Ca (‰)Δδb (‰)δpc (‰)δ13Cpfd (‰)SST-WRe (°C)SST-AOf (°C)δdg (‰)ɛph (‰)ɛfi (‰)K0j (mol L−1 atm−1)pCO2k (ppmv)
b = 160b = 200b = 240
  • a

    The average δ13C compositions of the indicated biomarkers.

  • b

    The isotopic offset between lipids and biomass for algae [Schouten et al., 1998; Massé et al., 2004; Oakes et al., 2005] and for cyanobacteria [Sakata et al., 1997].

  • c

    Estimated stable carbon isotopic composition of the primary photosynthate calculated from the δ13C composition of the biomarkers and Δδ.

  • d

    Average δ13C of inorganic carbonate of the planktonic foraminifer A. soldadoensis measured in sediments of Sites 1263, 1265, and 1267 at Walvis Ridge [Lourens et al., 2005; Stap et al., 2010].

  • e

    Average sea surface temperatures for Walvis Ridge obtained from the δ18O [Stap et al., 2010].

  • f

    Average sea surface temperatures obtained from TEX′86 [Sluijs et al., 2009] for the ACEX sediments at Arctic Ocean.

  • g

    The carbon isotopic composition of CO2(aq).

  • h

    The calculated isotopic fractionation associated with the photosynthetic fixation of carbon.

  • i

    The maximum isotopic fractionation associated with the photosynthetic fixation of carbon.

  • j

    The solubility constant K0 of Henry's Law from Weiss [1974].

  • k

    The calculated atmospheric CO2 concentration for three different b values.

Preexcursion Interval (369.60–368.94 mcd)
S-bound phytane−33.9 ± 0.46−27.9218.519−8.719.7250.0343190011001300
S-bound phytane−33.9 ± 0.46−27.9218.519−8.719.7270.03431650800950
S-bound HBI−33.3 ± 0.36−27.3218.519−8.719.1250.0343180010001200
S-bound HBI−33.3 ± 0.36−27.3218.519−8.719.1270.03431600750900
S-bound C35 hopane−31.5 ± 0.28.4−23.1218.519−8.714.7200.0343190011001350
Excursion Interval (368.84–368-72 mcd)
S-bound phytane−36.7 ± 0.46−30.7021.523−10.421.0250.0307130016501950
S-bound phytane−36.7 ± 0.46−30.7021.523−10.421.0270.030785011001300
S-bound HBI−36.7 ± 0.26−30.7021.523−10.420.9250.0307130016001900
S-bound HBI−36.7 ± 0.26−30.7021.523−10.420.9270.030785011001300
S-bound C35 hopane−35.1 ± 0.28.4−26.7021.523−10.416.8200.0307160020002400
Postexcursion Interval (368.20–368.04 mcd)
S-bound phytane−33.6 ± 0.26−27.61.517.518−9.318.8250.03537509001100
S-bound phytane−33.6 ± 0.26−27.61.517.518−9.318.8270.0353550700850
S-bound HBI−33.1 ± 0.26−27.11.517.518−9.318.2250.03536508501000
S-bound HBI−33.1 ± 0.26−27.11.517.518−9.318.2270.0353500650800
S-bound C35 hopane−32.5 ± 0.38.4−24.11.517.518−9.315.1200.035390011501400

[24] The magnitude of ɛp is mainly determined by the carbon fixation enzyme and carbonate concentration mechanism, which in turn can be affected by factors such as the amount of available CO2 in the water column ([CO2aq]), growth rate, light intensity, and species-specific factors such as cell geometry [e.g., Jasper and Hayes, 1990; Laws et al., 1995; Popp et al., 1998a, 1998b; Cassar et al., 2006]. Thus, in principle, the observed increase in biomarker ɛp values during ETM2 can be caused by increased levels of [CO2aq], but there are several additional factors which may be potentially responsible for this. The most important ones are a decrease in specific growth rates, a change in cell geometry, a change in light intensity, and the carbon uptake mechanism [Bidigare et al., 1997; Laws et al., 1995; Popp et al., 1998a, 1998b; Rau et al., 1996; Burkhardt et al., 1999]. It is unlikely that cell geometry has changed on this relative short time interval of the ETM2 for both the marine algae and (cyano)bacteria. Moreover, we also use S-bound phytane which is a biomarker not specific for only one group of organisms, but is contributed by many different species of marine algae and cyanobacteria. Furthermore, all available information indicates that productivity increased rather than decreased during ETM2 (see above), which theoretically should lead to a decrease of ɛp values. To avoid the imprint of growth rate changes on fractionation, we only used δ13C values before, and directly after the interval where several lines of evidence, including elevated biomarker concentrations, indicated elevated productivity (see section 4.1).

[25] Another important aspect to consider is the carbon uptake mechanism used by autotrophs during photosynthesis. Many photosynthetic organisms have evolved mechanisms to actively take up CO2 or HCO3 (a so-called carbon concentrating mechanism or CCM) in order to overcome the deficiency of the enzyme Rubisco in low-CO2/high-alkaline environments and this mechanism will impact a reduced isotopic fractionation [Giordano et al., 2005]. In our case, however, the time of ETM2 most likely belonged to a high-CO2/low-pH world, considering the large input of 13C-depleted carbon, making it unlikely that they need a CCM. Furthermore, isotopic modeling which incorporates active transport shows that ɛp is still a function of growth rate and CO2 under nutrient limitation (though this function is different under light limitation [Cassar et al., 2006]). Finally, the very negative biomarker δ13C values suggest that the organisms that made the lipids likely did not use a CCM, which has also been previously suggested for diatoms that biosynthesize HBI isomers [Schouten et al., 2000].

[26] Growth experiments of aquatic algae indicate that light-limitation may also have a potential effect on isotopic fractionation [Burkhardt et al., 1999; Cassar et al., 2006]. However, at this latitude it is likely that phytoplankton thrived only during summer in full light conditions, particularly with the absence of ice at this time. The only change in light conditions could appear when the water column is more stratified and fresher during ETM2, resulting in increasing light intensity and an increase in the magnitude of isotopic fractionation. However, the time of highest stratification, i.e., when isorenieratene derivatives are present, is some time after the CIE. In contrast, this interval is marked by slightly enriched 13C values for the different biomarkers. This suggests that light limitation cannot explain the isotopic fractionation patterns we observe. We, therefore, mostly attribute the increase in ɛp to a substantial increase in seawater CO2 concentration ([CO2aq]), in turn caused by elevated atmospheric pCO2 levels during ETM2.

4.4. A First Attempt to Estimate pCO2 for ETM2 Using Carbon Isotopic Fractionation Factors

[27] For alkenone-producing haptophytes the relationship between [CO2aq] and ɛp is relatively well constrained [Pagani et al., 2002, and references therein]. Therefore, stable carbon isotopic fractionation records using long-chain alkenones are frequently used for pCO2 reconstructions [e.g., Andersen et al., 1999; Benthien et al., 1999; Pagani et al., 1999, 2002, 2005; Pagani, 2002; Bijl et al., 2010; Palmer et al., 2010]. However, Popp et al. [1998b] also reported a relation between [CO2aq], growth rate and cell dimension for certain diatoms and cyanobacteria, although again other factors such as light intensity may play a role as well [Burkhardt et al., 1999; Cassar et al., 2006]. This would imply that the carbon isotope composition of specific marine algal biomarkers, other than alkenones, may also be applicable for pCO2 reconstructions. Indeed, ancient pCO2 levels were determined by Freeman and Hayes [1992] using the carbon isotopic fractionations of sedimentary porphyrins [Popp et al., 1989]. Furthermore, variations in the offset between carbonate and organic matter isotopic composition have been applied as paleo-pCO2 proxy to reconstruct the expected drawdown in atmospheric CO2 during the late Cenomanian oceanic anoxic event [Jarvis et al., 2011]. Their trend in isotopic fractionation is remarkably consistent with previously estimated Cretaceous pCO2 values using the δ13C values of the specific marine biomarkers (S-bound) phytane and C35 hopane [Bice et al., 2006; Sinninghe Damsté et al., 2008].

[28] Here we follow the approach of Freeman and Hayes [1992], Bice et al. [2006], and Sinninghe Damsté et al. [2008] to provide estimates of pCO2 during the early Eocene ETM2 interval. Large uncertainties and assumptions which are associated with this approach will be discussed below. Our goal here is merely to present estimates of the atmospheric CO2 concentrations and changes therein, which potentially can give insight in the changes of pCO2 levels across an Eocene hyperthermal, and provide a method which can be used at other environmental settings where similar isotopic biomarker records can be obtained.

4.4.1. Calculation of pCO2 Estimates

[29] In order to reconstruct the atmospheric CO2 concentrations across ETM2 from carbon isotopic fractionation factors, we assume that the relationship between ɛp and [CO2]aq, based on the calibration of δ13C composition of alkenones, is also applicable for δ13C values of other biomarkers produced by photoautotrophic organisms, in this case S-bound phytane, C25 HBI and C35 hopane. If so, then the degree of isotopic fractionation (ɛp) in a cell can in theory be related to CO2 concentrations using the following equation [Bidigare et al., 1997]:

display math

where b is the sum of species-specific factors and reflects the carbon demand of the cell. Atmospheric pCO2 concentrations can then be estimated from the [CO2(aq)] values using Henry's law.

[30] For haptophyte algae it has been shown that b displays a strong positive correlation with phosphate concentrations [Andersen et al., 1999; Benthien et al., 2002; Bidigare et al., 1997; Pagani et al., 2002], and thus, if phosphate concentrations were known then b, and thereby [CO2(aq)], could be estimated. A similar relation, with different b values, is observed for other algae [Popp et al., 1998b] and we assume here that b values of these algae also depend on nutrients such as phosphate. However, it is difficult to predict the PO4 concentrations of Arctic surface waters, especially considering the stratified conditions during ETM2. Andersen et al. [1999] reported an inverse relationship between the bulk nitrogen isotopes and phosphate concentrations in equatorial and south Atlantic core top sediments. They used this relationship to reconstruct b and in turn the pCO2 levels using their calibration of sedimentary δ13C alkenones. As an approach to constrain the b value for equation (3), we applied this relationship to the Early Eocene Arctic Ocean by using the nitrogen isotope values measured by Knies et al. [2008], leading to average phosphate concentrations of 1.25 μmol/L prior to ETM2 to 1.5 μmol/L just at the onset of ETM2. Depending on the calibration, this leads to a b value ranging between 160 to 240. The pCO2 estimates obtained using the approach outlined above are illustrated in Figure 4. Here we plotted the ɛp-CO2 relationship of the algal biomarkers for the three time intervals at an intermediate b value of 200. The error bars include uncertainties in SST (±1°C) and δ13Cpf (±0.5‰), in addition to the analytical errors. To illustrate the importance of b, we varied this parameter over a range of 160–240 (Table 3 and Figure 4). One has to bear in mind, though, that our pCO2 estimates are based on the ɛp-[CO2aq] relationship originally calibrated for δ13C alkenones [Pagani et al., 2002, and references therein]. In addition, we assume that the δ13Cpf from Walvis Ridge is a representative of that in the Arctic Ocean during the ETM2. The propagated uncertainty stemming from these assumptions is difficult to quantify and is further discussed below.

Figure 4.

Estimations of the atmospheric CO2 concentrations for the pre-ETM2 interval (green symbols), CIE of ETM2 (red symbols), and the post-ETM2 interval (blue symbols) using (a) the average δ13C values of C35 hopane (diamonds) using a maximum fractionation level (ɛf) of 20‰, (b) the average δ13C values of phytane (circles) and C25 HBI (triangles) with an ɛf of 25‰, and (c) the average δ13C values of phytane (circles) and C25 HBI (triangles) using an ɛf value of 27‰. Error bars include variations in SST and δ13Cpf of 1°C and 0.5‰, respectively, in addition to analytical errors. The gray shaded areas give the range of b (160–240) with b = 200 as intermediate value. Note that the uncertainty of the pCO2 estimates increases with higher ɛp values. Minimum pCO2 values using this approach are 590, 860, and 520 ppmv for the pre-ETM interval, the CIE of ETM2, and the post-ETM2 interval, respectively. This is at least two to three times preindustrial pCO2 levels (blue dotted line).

[31] For all three periods, the estimated pCO2 values are practically similar using three independent biomarkers and all suggest that pCO2 values were at least 2× preindustrial values, i.e., the minimum pCO2 estimates (considering all the uncertainties). Furthermore, when using the intermediate b value, the estimated pCO2 values are 800 to 1100 ppmv (3 to 4 times preindustrial values) for the preexcursion interval and 1100 to 2000 ppmv (4 to 7 times preindustrial values) for the CIE of ETM2 (see Table 3). Thus, pCO2 levels during ETM2 may have been 300 to 800 ppmv higher than prior to the ETM2.

4.4.2. Uncertainties, Caveats, and Future Outlook

[32] Clearly, our estimated pCO2 values are all associated with large uncertainties as indicated by the large error bars in Figure 4, and we caution that they should not be taken at face value. As mentioned before these pCO2 estimates are relying on a number of assumptions: (1) the δ13C composition of the DIC (δ13Cpf in equation (2)) of the Arctic Ocean surface waters equals the surface water δ13C of DIC of the subtropic SE Atlantic Ocean at Walvis Ridge during the Early Eocene; (2) the relationship between ɛp and [CO2]aq, based on the calibration of δ13C composition of alkenones, is also applicable for δ13C values of other biomarkers produced by photoautotrophic organisms, in this case S-bound phytane, C25 HBI and C35 hopane; and (3) the b value of photoautotrophs other than haptophyte algae are also related to nitrogen isotopic compositions. Since these assumptions have not yet been tested, it is not possible to estimate potential errors they introduce in the pCO2 estimates, but clearly they will have a large impact. Furthermore, there are a number of uncertainties associated with estimations of the isotopic fractionation factors as discussed in section 4.3. For example, an uncertainty in δ13Cpf may arise due to diagenesis and vital effects, and may be in the order of 0.5‰. An uncertainty of that magnitude will result in an equal uncertainty of 0.5‰ in ɛp. In turn, this will result in a significant error of the pCO2 estimations, which will be higher with higher ɛp values. The error caused by uncertainties in SST estimates is twofold. An increase of 1°C causes ɛp to increase with ∼0.12‰. The second uncertainty is in the sensitivity of the Arctic SST on the pCO2 estimates as the solubility of CO2 is higher under lower seawater temperatures. In comparison with uncertainties in δ13Cpf, an uncertainty in SST does not result in a large error in the pCO2 estimates (10–100 ppmv per 1°C) and depends on the amount of [CO2]aq. Thus, uncertainties in SST cause a relatively minor effect on our pCO2 estimates. Nevertheless, our ‘background’-ETM2 pCO2 estimates are in agreement with other estimates using proxy data [Demicco et al., 2003; Lowenstein and Demicco, 2006] and modeling [Berner and Kothavala, 2001; Pagani et al., 2006a; Zeebe et al., 2009] for the early/middle Eocene.

[33] Clearly, further research constraining the viability of this approach is needed. Especially, a good calibration between biomarker δ13C, ɛp and pCO2 based on modern microorganisms other than haptophytes, is essential to gain better insight in the factors that influence isotopic fractionation as discussed in the previous section. These calibrations are needed to test the assumptions that are at the base of our pCO2 reconstructions. Another way to test the reliability of our fractionation model is to compare estimated pCO2 using existing δ13C records of organic biomarkers with better-constrained pCO2 conditions during past intervals, such as the last glacial cycles. As a first step, we used the δ13C of biomarkers of C25 HBIs in Holocene sediments of the Arabian Sea [Schouten et al., 2000] to estimate preindustrial pCO2 levels using our method. We arrive at values between 250 to 300 ppmv, which compares favorably well with preindustrial pCO2 values (Table 4).

Table 4. The pCO2 Estimates Inferred From Diatom Biomarkers From Holocene Arabian Sea Sediments Sampled at Different Sitesa
SiteSST (°C)δ13C (‰)δd (‰)Biomarkerδ13C (‰)ɛp (‰)b (kg μmol−1 L)[CO2aq] (μmol kg−1)pCO2 (ppmv)
451252−8C25:0 HBI−23.39.51409.0310
453252−8C25:0 HBI−21.77.81408.1280
921252−8C25:3 HBI−19.96.01407.3250
921252−8C25:3 HBI−19.45.51407.2250
921252−8C25:4 HBI−21.77.81408.1280

5. Conclusions

[34] We measured concentrations and the δ13C composition of sulfur-bound biomarkers of marine algal and bacterial origin in sediments deposited in the Arctic Ocean during ETM2, which record environmental change and primary producer responses. Prior to ETM2, the depositional environment was eutrophic with anoxic bottom water conditions, evident from the high TOC content and the presence of sulfur-bound chemical fossils. The various biomarkers show a negative CIE of 3–4.5‰, synchronously with a CIE of 3.5‰ in δ13CTOC, confirming a decrease in the δ13C of the global exogenic carbon pool. Biomarker concentrations and carbon isotope records indicate that primary productivity increased during ETM2. This led to higher oxygen consumption and contributed to the development of photic zone euxinia. The CIE of the biomarkers is larger than that recorded in marine carbonates, suggesting an increase in the isotopic fractionation of the marine primary producers, likely due to elevated pCO2 levels. Using the carbon isotopic fractionation factors, we made a first attempt to reconstruct atmospheric CO2 concentrations and yield a potential range in pCO2 values of 800 to 1100 ppmv (3 to 4 × preindustrial values) and 1100 to >2000 ppmv (4 to >7 × preindustrial values) for the preexcursion and ETM2, respectively. However, these estimations are subjected to large limiting factors and uncertainties. Critically, to estimate carbon isotopic fractionation factors we adopted the surface water δ13C DIC values of Walvis Ridge as a representative of the Arctic Ocean surface waters during ETM2. In addition, our pCO2 estimates are based on the assumption that the ɛp-[CO2aq] relationship, originally calibrated for the δ13C composition of alkenones, is also applicable for other biomarkers. Therefore, our estimated pCO2 values should be considered with care. Rather, they are meant to give an idea on what scale pCO2 levels may have changed during an Eocene hyperthermal. A more thorough testing of the use of δ13C composition of biomarkers derived from marine microorganisms for pCO2 reconstructions is needed, before this method can be used as a tool for reconstructing pCO2 conditions of past climate.


[35] This research used samples and data provided by the Integrated Ocean Drilling Program (IODP). This is publication number DW-2011-1007 of the Darwin Center for Biogeosciences, which partially funded this project. A.S. thanks the Netherlands Organization for Scientific Research (NWO) for funding (Veni grant 863.07.001) and the European Research Council under the European Community's Seventh Framework Program for ERC Starting Grant 259627. We thank Jerry Dickens, Mark Pagani, and two anonymous reviewers for their critical comments on the manuscript and M. Kienhuis, J. Ossebaar, and A. Mets for their technical support.