Absolute sedimentary concentrations of highly branched isoprenoids, PIP25 indices with derived spring sea ice concentrations, and classification tree predictions of sea ice conditions in three Barents Sea sediment cores

• Main Authors: Köseoğlu, Denizcan, Belt, Simon T, Husum, Katrine, Knies, Jochen
• Format: Dataset
• Language: English
• Published: PANGAEA 2018
• Subjects: Arctic; Barents Sea; Climate change; Phytoplankton; Sea ice
• Online Access: https://doi.pangaea.de/10.1594/PANGAEA.891102; https://doi.org/10.1594/PANGAEA.891102

The development of various combinative methods for Arctic sea ice reconstruction using the sympagic highly-branched isoprenoid IP25 in conjunction with pelagic biomarkers has often facilitated more detailed descriptions of sea ice conditions than using IP25 alone. Here, we investigated the complementary application of the Phytoplankton-IP25 index (PIP25) and a recently proposed Classification Tree (CT) model for describing 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 highly-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 for future investigations.