Late Paleocene–early Eocene Arctic Ocean sea surface temperatures: reassessing biomarker paleothermometry at Lomonosov Ridge

Abstract

Abstract. A series of papers published shortly after the Integrated Ocean Drilling Program Arctic Coring Expedition (ACEX, 2004) on Lomonosov Ridge indicated remarkably high early Eocene sea surface temperatures (SSTs; ca. 23 to 27 ∘C) and land air temperatures (ca. 17 to 25 ∘C) based on the distribution of isoprenoid and branched glycerol dialkyl glycerol tetraether (isoGDGT and brGDGT) lipids, respectively. Here, we revisit these results using recent analytical developments – which have led to improved temperature calibrations and the discovery of new temperature-sensitive glycerol monoalkyl glycerol tetraethers (GMGTs) – and currently available proxy constraints. The isoGDGT assemblages support temperature as the dominant variable controlling TEX86 values for most samples. However, contributions of isoGDGTs from land, which we characterize in detail, complicate TEX86 paleothermometry in the late Paleocene and part of the interval between the Paleocene–Eocene Thermal Maximum (PETM; ∼ 56 Ma) and the Eocene Thermal Maximum 2 (ETM2; ∼ 54 Ma). Background early Eocene SSTs generally exceeded 20 ∘C, with peak warmth during the PETM (∼ 26 ∘C) and ETM2 (∼ 27 ∘C). We find abundant branched GMGTs, likely dominantly marine in origin, and their distribution responds to environmental change. Further modern work is required to test to what extent temperature and other environmental factors determine their distribution. Published Arctic vegetation reconstructions indicate coldest-month mean continental air temperatures of 6–13 ∘C, which reinforces the question of whether TEX86-derived SSTs in the Paleogene Arctic are skewed towards the summer season. The exact meaning of TEX86 in the Paleogene Arctic thus remains a fundamental issue, and it is one that limits our assessment of the performance of fully coupled climate models under greenhouse conditions.

OPTiMAL: a new machine learning approach for GDGT-based palaeothermometry

“…Both TEX H 86 and TEX L 86 were widely used and tested across a range of temperatures and palaeoenvironments, including comparisons against other palaeotemperature proxy systems (Hollis et al, 2012;Lunt et al, 2012;Bijl et al, 2013;Dunkley Jones et al, 2013;Zhang et al, 2014;Seki et al, 2014;Douglas et al, 2014;Linnert et al, 2014;Hertzberg et al, 2016). In certain environments TEX L 86 was subject to significant variability in derived temperatures that were not apparent in TEX H 86 (Taylor et al, 2013). This was mostly due to changing GDGT-2-to-GDGT-3 ratios, which strongly influence TEX L 86 , and may be related to local non-thermal environmental conditions at the site of GDGT production, and deep-water lipid production (Taylor et al, 2013).…”

“…In certain environments TEX L 86 was subject to significant variability in derived temperatures that were not apparent in TEX H 86 (Taylor et al, 2013). This was mostly due to changing GDGT-2-to-GDGT-3 ratios, which strongly influence TEX L 86 , and may be related to local non-thermal environmental conditions at the site of GDGT production, and deep-water lipid production (Taylor et al, 2013). As a result, TEX L 86 is no longer regarded as an appropriate tool for palaeotemperature reconstructions, except in limited polar conditions (Kim et al, 2010;Tierney, 2012).…”

“…The performances of Op1 and Op3 were very similar in most applications, except in applications to the palaeo-Arctic (see below), where the inclusion of modern Arctic calibration data (Op1) provided closer calibration constraints to the palaeo-data. Although the inclusion of modern Arctic data may well be beneficial for the study of high-latitude palaeoclimate archives, we are initially cautious as in this instance the deep-time palaeo-data have previously been rejected because of a potential bias by non-marine inputs indicated by high BIT indices (Sluijs et al, 2020). In this case there could be some consistency between the modern and ancient GDGT production by marine archaea in the Arctic which may help in the understanding of GDGT-based palaeothermometry in this unusual environment (Sluijs et al, 2020), but we recommend further investigation of the modern Arctic core-top biomarker assemblages before their regular inclusion into the calibration dataset.…”

“…The main exception to this is the BIT index in the Eocene dataset, where 15 samples have high BIT values (> 0.5) but have GDGT assemblages that are close to modern analogues in the calibration dataset (D nearest < 0.5). Of these samples, 9 are from the Arctic Ocean between the Paleocene-Eocene thermal maximum (PETM) and Eocene thermal maximum 2 (ETM2), an interval noted for its relatively high BIT index values (Sluijs et al, 2020); 3 are from the Eocene-Oligocene transition of ODP Site 1218 (eastern Equatorial Pacific) (Liu et al, 2009); 2 are from the middle Eocene of Seymour Island (Douglas et al, 2014); and 1 is from the late Eocene of DSDP Site 511, which has been already noted as an individual sample with anomalously high BIT in this dataset (Liu et al, 2009;Inglis et al, 2015). Although high BIT at ODP Site 1218 has been inferred to represent "relatively high terrestrial input" (Inglis et al, 2015) this seems unusual for a fully pelagic site situated on oceanic crust > 3000 km away from the nearest continental landmass.…”

“…The final example is from the latest Paleocene to early Eocene of IODP Expedition 302 Hole 4A on Lomonosov Ridge (Sluijs et al, 2006(Sluijs et al, , 2009(Sluijs et al, , 2020. This site is useful as it has been the focus of detailed reassessment and reanalysis, using most of the available screening methodologies to detect aberrant GDGT assemblages (Sluijs et al, 2020). Here we use this recently published data to compare the new D nearest screening metric against multiple other screening protocols (Fig.…”