An assessment of biomarker-based multivariate classification methods versus the PIP25 index for paleo Arctic sea ice reconstruction
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https://hdl.handle.net/10037/15039Date
2018-08-30Type
Journal articleTidsskriftartikkel
Peer reviewed
Abstract
The development of various combinative methods for Arctic sea ice reconstruction using the
sympagic highly-branched isoprenoid (HBI) IP25 in conjunction with pelagic biomarkers has
often facilitated more detailed descriptions of sea ice conditions than using IP25 alone. Here,
we investigated the application of the Phytoplankton-IP25 index (PIP25) and a recently
proposed Classification Tree (CT) model for describing temporal shifts in sea ice conditions
to assess the consistency of both methods. Based on biomarker data from three downcore
records from the Barents Sea spanning millennial timescales, we showcase apparent and
potential limitations of both approaches, and provide recommendations for their identification
or prevention. Both methods provided generally consistent outcomes and, within the studied
cores, captured abrupt shifts in sea ice regimes, such as those evident during the Younger
Dryas, as well as more gradual trends in sea ice conditions during the Holocene. The most
significant discrepancies occurred during periods of highly unstable climate change, such as
those characteristic of the Younger Dryas–Holocene transition. Such intervals of increased
discrepancy were identifiable by significant changes of HBI distributions and correlations to
values not observed in proximal surface sediments. We suggest that periods of highly36 fluctuating climate that are not represented in modern settings may hinder the performance
and complementary application of PIP25 and CT-based methods, and that data visualisation
techniques should be employed to identify such occurrences in downcore records.
Additionally, due to the reliance of both methods on biomarker distributions, we emphasise the importance of accurate and consistent biomarker quantification.
Description
Accepted manuscript version, licensed CC BY-NC-ND 4.0. Source at: http://doi.org/10.1016/j.orggeochem.2018.08.014