Sediment organic matter, grain size, and results of prediction models from northern North Atlantic and Arctic Seas ...
Sediment samples and hydrographic conditions were studied at 28 stations around Iceland. At these sites, Conductivity-Temperature-Depth (CTD) casts were coducted to collect hydrographic data and multicorer casts were conducted to collect data on sediment characteristics including grain size distribu...
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ftdatacite:10.1594/pangaea.831943 2024-03-31T07:51:05+00:00 Sediment organic matter, grain size, and results of prediction models from northern North Atlantic and Arctic Seas ... Ostmann, Alexandra Schnurr, Sarah Martínez Arbizu, Pedro 2014 application/zip https://dx.doi.org/10.1594/pangaea.831943 https://doi.pangaea.de/10.1594/PANGAEA.831943 en eng PANGAEA https://dx.doi.org/10.2478/popore-2014-0021 Creative Commons Attribution 3.0 Unported https://creativecommons.org/licenses/by/3.0/legalcode cc-by-3.0 Supplementary Publication Series of Datasets article Collection 2014 ftdatacite https://doi.org/10.1594/pangaea.83194310.2478/popore-2014-0021 2024-03-04T13:35:39Z Sediment samples and hydrographic conditions were studied at 28 stations around Iceland. At these sites, Conductivity-Temperature-Depth (CTD) casts were coducted to collect hydrographic data and multicorer casts were conducted to collect data on sediment characteristics including grain size distribution, carbon and nitrogen concentration, and chloroplastic pigment concentration. A total of 14 environmental predictors were used to model sediment characteristics around Iceland on regional scale. Two approaches were used: Multivariate Adaptation Regression Splines (MARS) and randomForest regression models. RandomForest outperformed MARS in predicting grain size distribution. MARS models had a greater tendency to over-and underpredict sediment values in areas outside the environmental envelope defined by the training dataset. We provide first GIS layers on sediment characteristics around Iceland, that can be used as predictors in future models. Although models performed well, more samples, especially from the ... : Supplement to: Ostmann, Alexandra; Schnurr, Sarah; Martínez Arbizu, Pedro (2014): Marine Environment Around Iceland: Hydrography, Sediments and First Predictive Models of Icelandic Deep-sea Sediment Characteristics. Polar Research Special Issue, Polish Polar Research, 35(2) ... Article in Journal/Newspaper Arctic Iceland North Atlantic Polish Polar Research DataCite Metadata Store (German National Library of Science and Technology) Arctic Martínez ENVELOPE(-62.183,-62.183,-64.650,-64.650) |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
English |
description |
Sediment samples and hydrographic conditions were studied at 28 stations around Iceland. At these sites, Conductivity-Temperature-Depth (CTD) casts were coducted to collect hydrographic data and multicorer casts were conducted to collect data on sediment characteristics including grain size distribution, carbon and nitrogen concentration, and chloroplastic pigment concentration. A total of 14 environmental predictors were used to model sediment characteristics around Iceland on regional scale. Two approaches were used: Multivariate Adaptation Regression Splines (MARS) and randomForest regression models. RandomForest outperformed MARS in predicting grain size distribution. MARS models had a greater tendency to over-and underpredict sediment values in areas outside the environmental envelope defined by the training dataset. We provide first GIS layers on sediment characteristics around Iceland, that can be used as predictors in future models. Although models performed well, more samples, especially from the ... : Supplement to: Ostmann, Alexandra; Schnurr, Sarah; Martínez Arbizu, Pedro (2014): Marine Environment Around Iceland: Hydrography, Sediments and First Predictive Models of Icelandic Deep-sea Sediment Characteristics. Polar Research Special Issue, Polish Polar Research, 35(2) ... |
format |
Article in Journal/Newspaper |
author |
Ostmann, Alexandra Schnurr, Sarah Martínez Arbizu, Pedro |
spellingShingle |
Ostmann, Alexandra Schnurr, Sarah Martínez Arbizu, Pedro Sediment organic matter, grain size, and results of prediction models from northern North Atlantic and Arctic Seas ... |
author_facet |
Ostmann, Alexandra Schnurr, Sarah Martínez Arbizu, Pedro |
author_sort |
Ostmann, Alexandra |
title |
Sediment organic matter, grain size, and results of prediction models from northern North Atlantic and Arctic Seas ... |
title_short |
Sediment organic matter, grain size, and results of prediction models from northern North Atlantic and Arctic Seas ... |
title_full |
Sediment organic matter, grain size, and results of prediction models from northern North Atlantic and Arctic Seas ... |
title_fullStr |
Sediment organic matter, grain size, and results of prediction models from northern North Atlantic and Arctic Seas ... |
title_full_unstemmed |
Sediment organic matter, grain size, and results of prediction models from northern North Atlantic and Arctic Seas ... |
title_sort |
sediment organic matter, grain size, and results of prediction models from northern north atlantic and arctic seas ... |
publisher |
PANGAEA |
publishDate |
2014 |
url |
https://dx.doi.org/10.1594/pangaea.831943 https://doi.pangaea.de/10.1594/PANGAEA.831943 |
long_lat |
ENVELOPE(-62.183,-62.183,-64.650,-64.650) |
geographic |
Arctic Martínez |
geographic_facet |
Arctic Martínez |
genre |
Arctic Iceland North Atlantic Polish Polar Research |
genre_facet |
Arctic Iceland North Atlantic Polish Polar Research |
op_relation |
https://dx.doi.org/10.2478/popore-2014-0021 |
op_rights |
Creative Commons Attribution 3.0 Unported https://creativecommons.org/licenses/by/3.0/legalcode cc-by-3.0 |
op_doi |
https://doi.org/10.1594/pangaea.83194310.2478/popore-2014-0021 |
_version_ |
1795029646014676992 |