Complementary biomarker-based methods for characterising Arctic sea ice conditions: A case study comparison between multivariate analysis and the PIP25 index
Accepted manuscript version. Published version available in Geochimica et Cosmochimica Acta, 222, 406-420. The discovery of IP25 as a qualitative biomarker proxy for Arctic sea ice and subsequent introduction of the so-called PIP25 index for semi-quantitative descriptions of sea ice conditions has s...
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Online Access: | https://hdl.handle.net/10037/12839 https://doi.org/10.1016/j.gca.2017.11.001 |
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ftunivtroemsoe:oai:munin.uit.no:10037/12839 2023-05-15T14:24:12+02:00 Complementary biomarker-based methods for characterising Arctic sea ice conditions: A case study comparison between multivariate analysis and the PIP25 index Koseoglu, Denizcan Belt, Simon T. Smik, Lukas Yao, Haoyi Panieri, Giuliana Knies, Jochen 2017-11-10 https://hdl.handle.net/10037/12839 https://doi.org/10.1016/j.gca.2017.11.001 eng eng Elsevier Geochimica et Cosmochimica Acta info:eu-repo/grantAgreement/RCN/SFF/223259/Norway/Centre for Arctic Gas Hydrate, Environment and Climate/CAGE/ Koseoglu, D., Belt, S. T., Smik, L., Yao, H., Panieri, G. & Knies, J. (2017). Complementary biomarker-based methods for characterising Arctic sea ice conditions: A case study comparison between multivariate analysis and the PIP25 index. Geochimica et Cosmochimica Acta, 222, 406-420. http://doi.org/10.1016/j.gca.2017.11.001 FRIDAID 1518998 doi:10.1016/j.gca.2017.11.001 0016-7037 1872-9533 https://hdl.handle.net/10037/12839 openAccess VDP::Matematikk og Naturvitenskap: 400::Geofag: 450::Kvartærgeologi glasiologi: 465 VDP::Matematikk og Naturvitenskap: 400::Geofag: 450 VDP::Mathematics and natural science: 400::Geosciences: 450 Journal article Tidsskriftartikkel Peer reviewed 2017 ftunivtroemsoe https://doi.org/10.1016/j.gca.2017.11.001 2021-06-25T17:55:43Z Accepted manuscript version. Published version available in Geochimica et Cosmochimica Acta, 222, 406-420. The discovery of IP25 as a qualitative biomarker proxy for Arctic sea ice and subsequent introduction of the so-called PIP25 index for semi-quantitative descriptions of sea ice conditions has significantly advanced our understanding of long-term paleo Arctic sea ice conditions over the past decade. We investigated the potential for classification tree1 (CT) models to provide a further approach to paleo Arctic sea ice reconstruction through analysis of a suite of highly branched isoprenoid (HBI) biomarkers in ca. 200 surface sediments from the Barents Sea. Four CT models constructed using different HBI assemblages revealed IP25 and an HBI triene as the most appropriate classifiers of sea ice conditions, achieving a >90% cross-validated classification rate. Additionally, lower model performance for locations in the Marginal Ice Zone (MIZ) highlighted difficulties in characterisation of this climatically-sensitive region. CT model classification and semi-quantitative PIP25- derived estimates of spring sea ice concentration (SpSIC) for four downcore records from the region were consistent, although agreement between proxy and satellite/observational records was weaker for a core from the west Svalbard margin, likely due to the highly variable sea conditions. The automatic selection of appropriate biomarkers for description of sea ice conditions, quantitative model assessment, and insensitivity to the c-factor used in the calculation of the PIP25 index are key attributes of the CT approach, and we provide an initial comparative assessment between these potentially complementary methods. The CT model should be capable of generating longer-term temporal shifts in sea ice conditions for the climatically sensitive Barents Sea. Article in Journal/Newspaper Arctic Arctic Barents Sea Paleo-Arctic Sea ice Svalbard Svalbard margin University of Tromsø: Munin Open Research Archive Arctic Barents Sea Svalbard Geochimica et Cosmochimica Acta 222 406 420 |
institution |
Open Polar |
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University of Tromsø: Munin Open Research Archive |
op_collection_id |
ftunivtroemsoe |
language |
English |
topic |
VDP::Matematikk og Naturvitenskap: 400::Geofag: 450::Kvartærgeologi glasiologi: 465 VDP::Matematikk og Naturvitenskap: 400::Geofag: 450 VDP::Mathematics and natural science: 400::Geosciences: 450 |
spellingShingle |
VDP::Matematikk og Naturvitenskap: 400::Geofag: 450::Kvartærgeologi glasiologi: 465 VDP::Matematikk og Naturvitenskap: 400::Geofag: 450 VDP::Mathematics and natural science: 400::Geosciences: 450 Koseoglu, Denizcan Belt, Simon T. Smik, Lukas Yao, Haoyi Panieri, Giuliana Knies, Jochen Complementary biomarker-based methods for characterising Arctic sea ice conditions: A case study comparison between multivariate analysis and the PIP25 index |
topic_facet |
VDP::Matematikk og Naturvitenskap: 400::Geofag: 450::Kvartærgeologi glasiologi: 465 VDP::Matematikk og Naturvitenskap: 400::Geofag: 450 VDP::Mathematics and natural science: 400::Geosciences: 450 |
description |
Accepted manuscript version. Published version available in Geochimica et Cosmochimica Acta, 222, 406-420. The discovery of IP25 as a qualitative biomarker proxy for Arctic sea ice and subsequent introduction of the so-called PIP25 index for semi-quantitative descriptions of sea ice conditions has significantly advanced our understanding of long-term paleo Arctic sea ice conditions over the past decade. We investigated the potential for classification tree1 (CT) models to provide a further approach to paleo Arctic sea ice reconstruction through analysis of a suite of highly branched isoprenoid (HBI) biomarkers in ca. 200 surface sediments from the Barents Sea. Four CT models constructed using different HBI assemblages revealed IP25 and an HBI triene as the most appropriate classifiers of sea ice conditions, achieving a >90% cross-validated classification rate. Additionally, lower model performance for locations in the Marginal Ice Zone (MIZ) highlighted difficulties in characterisation of this climatically-sensitive region. CT model classification and semi-quantitative PIP25- derived estimates of spring sea ice concentration (SpSIC) for four downcore records from the region were consistent, although agreement between proxy and satellite/observational records was weaker for a core from the west Svalbard margin, likely due to the highly variable sea conditions. The automatic selection of appropriate biomarkers for description of sea ice conditions, quantitative model assessment, and insensitivity to the c-factor used in the calculation of the PIP25 index are key attributes of the CT approach, and we provide an initial comparative assessment between these potentially complementary methods. The CT model should be capable of generating longer-term temporal shifts in sea ice conditions for the climatically sensitive Barents Sea. |
format |
Article in Journal/Newspaper |
author |
Koseoglu, Denizcan Belt, Simon T. Smik, Lukas Yao, Haoyi Panieri, Giuliana Knies, Jochen |
author_facet |
Koseoglu, Denizcan Belt, Simon T. Smik, Lukas Yao, Haoyi Panieri, Giuliana Knies, Jochen |
author_sort |
Koseoglu, Denizcan |
title |
Complementary biomarker-based methods for characterising Arctic sea ice conditions: A case study comparison between multivariate analysis and the PIP25 index |
title_short |
Complementary biomarker-based methods for characterising Arctic sea ice conditions: A case study comparison between multivariate analysis and the PIP25 index |
title_full |
Complementary biomarker-based methods for characterising Arctic sea ice conditions: A case study comparison between multivariate analysis and the PIP25 index |
title_fullStr |
Complementary biomarker-based methods for characterising Arctic sea ice conditions: A case study comparison between multivariate analysis and the PIP25 index |
title_full_unstemmed |
Complementary biomarker-based methods for characterising Arctic sea ice conditions: A case study comparison between multivariate analysis and the PIP25 index |
title_sort |
complementary biomarker-based methods for characterising arctic sea ice conditions: a case study comparison between multivariate analysis and the pip25 index |
publisher |
Elsevier |
publishDate |
2017 |
url |
https://hdl.handle.net/10037/12839 https://doi.org/10.1016/j.gca.2017.11.001 |
geographic |
Arctic Barents Sea Svalbard |
geographic_facet |
Arctic Barents Sea Svalbard |
genre |
Arctic Arctic Barents Sea Paleo-Arctic Sea ice Svalbard Svalbard margin |
genre_facet |
Arctic Arctic Barents Sea Paleo-Arctic Sea ice Svalbard Svalbard margin |
op_relation |
Geochimica et Cosmochimica Acta info:eu-repo/grantAgreement/RCN/SFF/223259/Norway/Centre for Arctic Gas Hydrate, Environment and Climate/CAGE/ Koseoglu, D., Belt, S. T., Smik, L., Yao, H., Panieri, G. & Knies, J. (2017). Complementary biomarker-based methods for characterising Arctic sea ice conditions: A case study comparison between multivariate analysis and the PIP25 index. Geochimica et Cosmochimica Acta, 222, 406-420. http://doi.org/10.1016/j.gca.2017.11.001 FRIDAID 1518998 doi:10.1016/j.gca.2017.11.001 0016-7037 1872-9533 https://hdl.handle.net/10037/12839 |
op_rights |
openAccess |
op_doi |
https://doi.org/10.1016/j.gca.2017.11.001 |
container_title |
Geochimica et Cosmochimica Acta |
container_volume |
222 |
container_start_page |
406 |
op_container_end_page |
420 |
_version_ |
1766296663158161408 |