{"dcterms:modified":"2026-04-24","dcterms:creator":"DataverseNO","@type":"ore:ResourceMap","schema:additionalType":"Dataverse OREMap Format v1.0.1","dvcore:generatedBy":{"@type":"schema:SoftwareApplication","schema:name":"Dataverse","schema:version":"6.6","schema:url":"https://github.com/iqss/dataverse"},"@id":"https://dataverse.no/api/datasets/export?exporter=OAI_ORE&persistentId=https://doi.org/10.18710/K3CDJJ","ore:describes":{"citation:keyword":[{"citation:keywordValue":"X-ray fluorescence","citation:keywordVocabulary":"Biological Imaging Methods Ontology","citation:keywordVocabularyURI":"http://purl.obolibrary.org/obo/FBbi_00000608"},{"citation:keywordValue":"Computed tomography","citation:keywordVocabulary":"EFO","citation:keywordVocabularyURI":"http://www.ebi.ac.uk/efo/EFO_0003960"},{"citation:keywordValue":"Grain-size"},{"citation:keywordValue":"End Member Modelling Analysis"},{"citation:keywordValue":"Sedimentology"},{"citation:keywordValue":"Geochemistry"},{"citation:keywordValue":"Lake sediment","citation:keywordVocabulary":"ENVO","citation:keywordVocabularyURI":"http://purl.obolibrary.org/obo/ENVO_00000546"},{"citation:keywordValue":"Eolian sediment"},{"citation:keywordValue":"Westerly winds"},{"citation:keywordValue":"Paleoclimate"},{"citation:keywordValue":"Paleoreconstructions"},{"citation:keywordValue":"Paleolimnology"},{"citation:keywordValue":"Holocene"},{"citation:keywordValue":"Arctic environment","citation:keywordVocabulary":"SNOMED","citation:keywordVocabularyURI":"http://snomed.info/id/284564007"},{"citation:keywordValue":"Spitsbergen"},{"citation:keywordValue":"Svalbard"},{"citation:keywordValue":"Loess"},{"citation:keywordValue":"High latitude dust"}],"citation:distributor":{"citation:distributorName":"University of Bergen","citation:distributorAbbreviation":"UiB","citation:distributorURL":"https://dataverse.no/dataverse/uib"},"citation:producer":[{"citation:producerName":"University of Szczecin","citation:producerAffiliation":"Institute of Marine and Environmental Sciences, Doctoral School","citation:producerAbbreviation":"UiB"},{"citation:producerName":"University of Bergen","citation:producerAffiliation":"Department of Earth Science and Bjerknes Centre for Climate Research, University of Bergen, Centre for Deep Sea Research, Department of Earth Science","citation:producerAbbreviation":"UiB"},{"citation:producerName":"University Centre in Svalbard","citation:producerAffiliation":"Department of Arctic Geology","citation:producerAbbreviation":"UNiS"},{"citation:producerName":"University of South Bohemia","citation:producerAffiliation":"Centre for Polar Ecology, Faculty of Science","citation:producerAbbreviation":"USB"},{"citation:producerName":"University of Wrocław","citation:producerAffiliation":"Alfred Jahn Cold Regions Research Centre, Institute of Geography and Regional Development","citation:producerAbbreviation":"UWr"}],"citation:datasetContact":{"citation:datasetContactName":"Zofia Stachowska","citation:datasetContactAffiliation":"Institute of Marine and Environmental Sciences, Doctoral School, University of Szczecin, Poland","citation:datasetContactEmail":"zofia.stachowska@usz.edu.pl"},"citation:dsDescription":[{"citation:dsDescriptionValue":"This dataset includes sediment analyses performed on core DST-2023-GC (78º27’N, 16º41’E, ~65 m a.s.l.) from Dunsappietjørna – a lake in Gipsdalen, Central Svalbard. The core was extracted during the summer of 2023 using a UWITEC gravity corer and analyzed throughout 2023-2025 to reconstruct the eolian signal in this sheltered inner-fjord-valley setting. The ~120.5 cm-long record dates back to ca. 8,200 cal. yrs B.P. Additionally, in the summer of 2024, we collected four sediment catchment samples (CS 1-4) and analysed them together with the core record.\n\nThe data are organized by figures and tables, in .txt format and contain all the original data presented in the main manuscript and its supplement. Additional details and references relevant to this replication data may also be found herein, in the appended README and REFERENCES files, respectively.","citation:dsDescriptionDate":"2026-03-30"},{"citation:dsDescriptionValue":"ABSTRACT: The Arctic is warming faster than any other region on Earth. As sea-ice diminishes, surface boundary conditions (roughness and air-sea coupling) change and open-water fetch increases, potentially strengthening the effective wind forcing on Arctic coasts. These changes can be recorded in lake sediments through the deposition of wind-blown grains and elements, offering insights into past wind and climate dynamics. We reconstruct ca. 8,200 yrs of wind-climate variability using laminated sediments from a closed-basin lake in the Central part of the High Arctic Svalbard archipelago. By integrating geochemical, visual, and granulometric fingerprints within a multiproxy geostatistical framework, we link wind-blown minerogenic input to specific catchment sources and show that iron (Fe)- and titanium (Ti)- enriched clasts originate from distinct dolerite outcrops West of the lake, upwind of the dominant summer Westerlies. These results reveal a locally filtered Westerly input, consistent with valley-fjord channelling. We identify four Mid- and Late Holocene phases of enhanced eolian activity that occurred during intervals when local boundary conditions favoured the entrainment and transport of sediment into the basin. Unit-scale sedimentation shifts can be placed at the end of the Holocene optimum and at the stepwise onset of the Neoglacial. However, the reconstructed wind signal shows comparatively stable long-term behaviour and no direct correspondence with paleoclimate records.","citation:dsDescriptionDate":"2026-04-21"}],"author":{"citation:authorName":"Stachowska, Zofia","citation:authorAffiliation":"Institute of Marine and Environmental Sciences, Doctoral School, University of Szczecin, Poland","authorIdentifierScheme":"ORCID","authorIdentifier":{"personName":"Stachowska, Zofia","@id":"https://orcid.org/0000-0001-7124-9231","scheme":"ORCID","@type":"https://schema.org/Person"}},"dateOfDeposit":"2026-03-30","subject":"Earth and Environmental Sciences","citation:depositor":"Stachowska, Zofia","title":"Replication Data for \"Geochemical and granulometric fingerprints of 8,200-year Westerly variability recorded in inner-fjord lake sediments from Central Svalbard\"","grantNumber":[{"citation:grantNumberAgency":"The Polish National Science Centre: ‘ASPIRE - Arctic storm impacts recorded in beach-ridges and lake archives: scenarios for less icy future’","citation:grantNumberValue":"No. UMO-2020/37/B/ST10/03074"},{"citation:grantNumberAgency":"HarSval Bilateral initiative aiming at a Harmonisation of the Svalbard cooperation and activities funding from the means of the EEA and Norway Grants 2014-2021","citation:grantNumberValue":"No. UMO-2023/43/7/ST10/00001"},{"citation:grantNumberAgency":"Polish Ministry of Science and Higher Education’s Regional Excellence Initiative Programme","citation:grantNumberValue":"No. 3/D/2025"},{"citation:grantNumberAgency":"The Trond Mohn Stiftelse: Starting Grant","citation:grantNumberValue":"No. TMS2021STG01"}],"geospatial:geographicCoverage":{"geospatial:country":"Norway","geospatial:state":"Svalbard"},"citation:dateOfCollection":{"citation:dateOfCollectionStart":"2023-09-01","citation:dateOfCollectionEnd":"2026-03-30"},"publication":{"publicationIDType":"doi","publicationURL":"https://doi.org/10.31223/X5719B"},"software":[{"citation:softwareName":"Thermo Scientific Pathfinder X-ray Microanalysis"},{"citation:softwareName":"GRADISTAT"},{"citation:softwareName":"AnalySize","citation:softwareVersion":"1.2.2"},{"citation:softwareName":"Adobe Illustrator","citation:softwareVersion":"15"},{"citation:softwareName":"MATLAB"},{"citation:softwareName":"ThermoFisher Avizo","citation:softwareVersion":"2"},{"citation:softwareName":"QAnalySeries"},{"citation:softwareName":"Grapher","citation:softwareVersion":"8"},{"citation:softwareName":"Adobe Illustrator","citation:softwareVersion":"2015"},{"citation:softwareName":"PAST","citation:softwareVersion":"4"},{"citation:softwareName":"CoDaPack"},{"citation:softwareName":"Bacon","citation:softwareVersion":"3.2.0"},{"citation:softwareName":"R","citation:softwareVersion":"2.5.0"},{"citation:softwareName":"QGIS","citation:softwareVersion":"3.34"}],"otherReferences":["Adobe. Creative, marketing and document management solutions https://www.adobe.com/ (2015) (accessed in July 2025).","Bertrand, S., Tjallingii, R., Kylander, M. E., Wilhelm, B., Roberts, S. J., Arnaud, F., Brown, E., and Bindler, R.: Inorganic geochemistry of lake sediments: A review of analytical techniques and guidelines for data interpretation, Earth-Science Reviews, 249, 104639, https://doi.org/10.1016/j.earscirev.2023.104639 (2024).","van der Bilt, W. G. M., Rea, B., Spagnolo, M., Roerdink, D. L., Jørgensen, S. L., and Bakke, J.: Novel sedimentological fingerprints link shifting depositional processes to Holocene climate transitions in East Greenland, Global and Planetary Change, 164, 52–64, https://doi.org/10.1016/j.gloplacha.2018.03.007 (2018).","Blaauw, M. et al. rbacon: Age-Depth Modelling using Bayesian Statistics. (2022).","Blott, S. J. & Pye, K. GRADISTAT: a grain size distribution and statistics package for the analysis of unconsolidated sediments. Earth Surf. Process. Landforms 26, 1237–1248 (2001).","Comas, M. & Thió Fernández de Henestrosa, S. CoDaPack 2.0: a stand-alone, multi-platform compositional software. in (CIMNE, 2011).","Cox Analytical System: Itrax Core Scanner: Q-Spec 6.5.2. Software Manual. Mölndal, 13 pp (2008).","ChiPlot. https://www.chiplot.online/ (accessed in July 2025).","Davies, S. J., Lamb, H. F., and Roberts, S. J.: Micro-XRF Core Scanning in Palaeolimnology: Recent Developments, in: Micro-XRF Studies of Sediment Cores: Applications of a non-destructive tool for the environmental sciences, edited by: Croudace, I. W. and Rothwell, R. G., Springer Netherlands, Dordrecht, 189–226, https://doi.org/10.1007/978-94-017-9849-5_7 (2015).","Dean, W. E. J. Determination of Carbonate and Organic Matter in Calcareous Sediments and Sedimentary Rocks by Loss on Ignition: Comparison With Other Methods. SEPM JSR Vol. 44, (1974).","Dietze, M., Schulte, P. & Dietze, E. Application of end-member modelling to grain-size data: Constraints and limitations. Sedimentology 69, 845–863 (2022).","Element — Oxide Conversions: https://meteorites.wustl.edu/goodstuff/oxides.htm, last access: 26 November 2023.","Golden Software Grapher https://www.goldensoftware.com/products/grapher/ (accessed in July 2025).","Goslar, T., Czernik, J. & Goslar, E. Low-energy 14C AMS in Poznań Radiocarbon Laboratory, Poland. Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms 223–224, 5–11 (2004).","Hammer, Ø., Harper, D. A. T. & Ryan, P. D. PAST: PALEONTOLOGICAL STATISTICS SOFTWARE PACKAGE FOR EDUCATION AND DATA ANALYSIS. https://palaeo-electronica.org/2001_1/past/issue1_01.htm (2001).","Heiri, O., Lotter, A. F. & Lemcke, G. Loss on ignition as a method for estimating organic and carbonate content in sediments: reproducibility and comparability of results. 10 (2001).","Hobday, A. J., Alexander, L. V., Perkins, S. E., Smale, D. A., Straub, S. C., Oliver, E. C. J., Benthuysen, J. A., Burrows, M. T., Donat, M. G., Feng, M., Holbrook, N. J., Moore, P. J., Scannell, H. A., Sen Gupta, A., and Wernberg, T.: A hierarchical approach to defining marine heatwaves, Progress in Oceanography, 141, 227–238, https://doi.org/10.1016/j.pocean.2015.12.014 (2016).","Itamiya, H., Sugita, R., and Sugai, T.: Analysis of the surface microtextures and morphologies of beach quartz grains in Japan and implications for provenance research, Prog Earth Planet Sci, 6, 43, https://doi.org/10.1186/s40645-019-0287-9 (2019).","Kotov, S. & Pälike, H. QAnalySeries – a cross-platform time series tuning and analysis tool. Earth and Space Science Open Archive https://essopenarchive.org/doi/full/10.1002/essoar.10500226.1 (2018) doi:10.1002/essoar.10500226.1.","Malvern Panalytical: Mastersizer 3000 User Manual English (2015).","Marshall, J. R., Bull, P. A., and Morgan, R. M.: Energy regimes for aeolian sand grain surface textures, Sedimentary Geology, 253–254, 17–24, https://doi.org/10.1016/j.sedgeo.2012.01.001 (2012).","Newbury, D. E. and Ritchie, N. W. M.: Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive X-ray spectrometry (SEM/SDD-EDS), J Mater Sci, 50, 493–518, https://doi.org/10.1007/s10853-014-8685-2 (2015).","Nyall Dawson, Jürgen Fischer, Matthias Kuhn, Alessandro Pasotti, mhugent, Denis Rouzaud, Alexander Bruy, Tim Sutton, Martin Dobias, Mathieu Pellerin, Even Rouault, Víctor Olaya, Paul Blottiere, Werner Macho, Radim Blazek, Gary Sherman, Harrissou Sant-anna, Julien Cabieces, Loïc Bartoletti, Nathan Woodrow, signedav, rldhont, Stefanos Natsis, Larry Shaffer, Nedjima Belgacem, Sandro Santilli, Salvatore Larosa, Sandro Mani, Jean Felder, and Vincent Cloarec: qgis/QGIS: 3.44.7, , https://doi.org/10.5281/ZENODO.6139224 (2026).","Paterson, G. A. & Heslop, D. New methods for unmixing sediment grain size data. Geochemistry, Geophysics, Geosystems 16, 4494–4506 (2015).","Perkins-Kirkpatrick, S. E. and Lewis, S. C.: Increasing trends in regional heatwaves, Nat Commun, 11, 3357, https://doi.org/10.1038/s41467-020-16970-7 (2020).","Porter, C., Howat, I., Noh, M.-J., Husby, E., Khuvis, S., Danish, E., Tomko, K., Gardiner, J., Negrete, A., Yadav, B., Klassen, J., Kelleher, C., Cloutier, M., Bakker, J., Enos, J., Arnold, G., Bauer, G., and Morin, P.: ArcticDEM - Mosaics, Version 4.1 (1.0), https://doi.org/10.7910/DVN/3VDC4W (2023).","Prins, M. A. & Weltje, G. J. End-member modeling of siliciclastic grain-size distributions: The late Quaternary record of aeolian and fluvial sediment supply to the Arabian Sea and its paleoclimatic significance. in Numerical experiments in stratigraphy: Recent advances in stratigraphic and sedimentologic computer simulations (ed. Harbaugh, J.) 91–111 (Society for Sedimentary Geology, 1999).","Reimer, P. J. et al. The IntCal20 Northern Hemisphere Radiocarbon Age Calibration Curve (0–55 cal kBP). Radiocarbon 62, 725–757 (2020).","Rothwell, R. G. and Croudace, I. w.: Twenty Years of XRF Core Scanning Marine Sediments: What Do Geochemical Proxies Tell Us?, in: Micro-XRF Studies of Sediment Cores: Applications of a non-destructive tool for the environmental sciences, edited by: Croudace, I. W. and Rothwell, R. G., Springer Netherlands, Dordrecht, 25–102, https://doi.org/10.1007/978-94-017-9849-5_2 (2015).","Thermo Fisher Scientific Avizo Software https://www.thermofisher.com/no/en/home/electron-microscopy/products/software-em-3d-vis/avizo-software.html (accessed in November 2024).","Thermo Fisher Scientific Inc. Pathfinder X-ray Microanalysis Software https://www.thermofisher.com/pathfinder (accessed in September 2024 and February-March 2025).","Toonen, W. H. J., Winkels, T. G., Cohen, K. M., Prins, M. A., and Middelkoop, H.: Lower Rhine historical flood magnitudes of the last 450years reproduced from grain-size measurements of flood deposits using End Member Modelling, CATENA, 130, 69–81, https://doi.org/10.1016/j.catena.2014.12.004 (2015).","Vos, K., Vandenberghe, N., and Elsen, J.: Surface textural analysis of quartz grains by scanning electron microscopy (SEM): From sample preparation to environmental interpretation, Earth-Science Reviews, 128, 93–104, https://doi.org/10.1016/j.earscirev.2013.10.013 (2014)."],"@id":"https://doi.org/10.18710/K3CDJJ","@type":["ore:Aggregation","schema:Dataset"],"schema:version":"1.0","schema:name":"Replication Data for \"Geochemical and granulometric fingerprints of 8,200-year Westerly variability recorded in inner-fjord lake sediments from Central Svalbard\"","schema:dateModified":"2026-04-24 13:01:33.421","schema:datePublished":"2026-04-24","schema:creativeWorkStatus":"RELEASED","schema:license":"http://creativecommons.org/publicdomain/zero/1.0","dvcore:fileTermsOfAccess":{"dvcore:fileRequestAccess":true},"schema:includedInDataCatalog":"DataverseNO","schema:isPartOf":{"schema:name":"University of Bergen","@id":"https://dataverse.no/dataverse/uib","schema:isPartOf":{"schema:name":"DataverseNO","@id":"https://dataverse.no/dataverse/root"}},"ore:aggregates":[{"schema:name":"00_Stach_2026_README.txt","dvcore:restricted":false,"dvcore:directoryLabel":"1","schema:version":1,"dvcore:datasetVersionId":5646,"@id":"doi:10.18710/K3CDJJ/GJ7E4K","schema:sameAs":"https://dataverse.no/api/access/datafile/:persistentId?persistentId=doi:10.18710/K3CDJJ/GJ7E4K","@type":"ore:AggregatedResource","schema:fileFormat":"text/plain","dvcore:filesize":36116,"dvcore:storageIdentifier":"S3://uit-dataverseno-prod01:19d9beca446-eca40196dde2","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"4951bf4520f1fed79478b22095d82bdb"}},{"schema:description":"This file contains all references cited in square brackets [x] in the '00_Stach_2026_README' file.","schema:name":"01_Stach_2026_references_README.txt","dvcore:restricted":false,"dvcore:directoryLabel":"2","schema:version":2,"dvcore:datasetVersionId":5646,"@id":"doi:10.18710/K3CDJJ/VA0DEN","schema:sameAs":"https://dataverse.no/api/access/datafile/:persistentId?persistentId=doi:10.18710/K3CDJJ/VA0DEN","@type":"ore:AggregatedResource","schema:fileFormat":"text/plain","dvcore:filesize":7584,"dvcore:storageIdentifier":"S3://uit-dataverseno-prod01:19d9bdef9df-d6ac7a2c5f35","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"1d9433df9b6ae22c534195efe98efffc"}},{"schema:description":"This file contains downcore ages (cal. yrs B.P.) and Sediment Accumulation Rates (SAR) presented in Figure 2, PANELS A-B. Ages are based on the radiocarbon (14C) chronology, calibrated with the Bayesian MCMC algorithm in Bacon v. 3.2.0, in R package v. 2.5.0 and the use of IntCal20 Northern Hemisphere Radiocarbon Age Calibration Curve (Blaauw et al., 2022; Reimer et al., 2020).","schema:name":"Stach_2026_Fig_2_chronology.txt","dvcore:restricted":false,"dvcore:directoryLabel":"3","schema:version":3,"dvcore:datasetVersionId":5646,"@id":"doi:10.18710/K3CDJJ/GI7XDN","schema:sameAs":"https://dataverse.no/api/access/datafile/:persistentId?persistentId=doi:10.18710/K3CDJJ/GI7XDN","@type":"ore:AggregatedResource","schema:fileFormat":"text/plain","dvcore:filesize":118778,"dvcore:storageIdentifier":"S3://uit-dataverseno-prod01:19d86a229cd-b910d30b759a","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"427fc4ef3370c85b538fc57b817a90c0"}},{"schema:description":"This file contains data presented in Figure 3. High-resolution data (0.02 and 0.05 cm, respectively) were obtained by X-Ray Fluorescence (XRF) and Computed Tomography (CT) scanning, while physical proxies (n=121) were calculated from material sampled at contiguous 1 cm intervals using a 0.3 cm-wide syringe.","schema:name":"Stach_2026_Fig_3_stratigraphy.txt","dvcore:restricted":false,"dvcore:directoryLabel":"4","schema:version":2,"dvcore:datasetVersionId":5646,"@id":"doi:10.18710/K3CDJJ/EMCF76","schema:sameAs":"https://dataverse.no/api/access/datafile/:persistentId?persistentId=doi:10.18710/K3CDJJ/EMCF76","@type":"ore:AggregatedResource","schema:fileFormat":"text/plain","dvcore:filesize":1231734,"dvcore:storageIdentifier":"S3://uit-dataverseno-prod01:19d86a22b03-ed1735bb5725","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"81858a7f94c59b55931ab182157c4b20"}},{"schema:description":"This file contains the output of Principal Component Analysis (PCA) performed on selected proxy parameters (n=121) to examine shared gradients of change. The analysis was performed in PAST v. 4 (Hammer et al., 2001). We selected the following variables: Computed Tomography (CT) grayscale, Dry Bulk Density (DBD), Loss On Ignition (LOI), centred-log ratio of Iron (clr Fe), clr Titanium (Ti), and clr Calcium (Ca), and logarithmic (log) abundances of End Members (EMs) 1-3.","schema:name":"Stach_2026_Fig_4_PCA.txt","dvcore:restricted":false,"dvcore:directoryLabel":"5","schema:version":2,"dvcore:datasetVersionId":5646,"@id":"doi:10.18710/K3CDJJ/15XTLL","schema:sameAs":"https://dataverse.no/api/access/datafile/:persistentId?persistentId=doi:10.18710/K3CDJJ/15XTLL","@type":"ore:AggregatedResource","schema:fileFormat":"text/plain","dvcore:filesize":2721,"dvcore:storageIdentifier":"S3://uit-dataverseno-prod01:19d8d079102-7b0411454c18","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"dd8ab0f7ff5e000645366911b857fb11"}},{"schema:description":"This file contains Energy-Dispersive X-ray Spectroscopy (SEM-EDS) output, used to map and quantify elemental and oxide compositions at the grain level (Newbury and Ritchie, 2015). Except for PANELS A-B, we excluded carbon (C) and oxygen (O) via manual deselection in Pathfinder v. 2.11 for all SEM-EDS analyses, and converted the results to oxides (wt%) following Element — Oxide Conversions (2023).","schema:name":"Stach_2026_Fig_5_SEM_EDS.txt","dvcore:restricted":false,"dvcore:directoryLabel":"6","schema:version":3,"dvcore:datasetVersionId":5646,"@id":"doi:10.18710/K3CDJJ/W4GC2W","schema:sameAs":"https://dataverse.no/api/access/datafile/:persistentId?persistentId=doi:10.18710/K3CDJJ/W4GC2W","@type":"ore:AggregatedResource","schema:fileFormat":"text/plain","dvcore:filesize":150923,"dvcore:storageIdentifier":"S3://uit-dataverseno-prod01:19d8d1ed956-ecb46ee1cc83","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"499fa45734ddfc8db71710c3064cde18"}},{"schema:description":"This file contains the hypsometry of mapped dolerite outcrops at Gåsøyane, Gipshuksletta, and Kapp Thorsden, derived from ArcticDEM at 2 m resolution in QGIS v. 3.34 (Nyall Dawson et al., 2026; Porter et al., 2023).","schema:name":"Stach_2026_Fig_6_dolerite_cumulative_submerged_areas.txt","dvcore:restricted":false,"dvcore:directoryLabel":"7","schema:version":2,"dvcore:datasetVersionId":5646,"@id":"doi:10.18710/K3CDJJ/KBHTBX","schema:sameAs":"https://dataverse.no/api/access/datafile/:persistentId?persistentId=doi:10.18710/K3CDJJ/KBHTBX","@type":"ore:AggregatedResource","schema:fileFormat":"text/plain","dvcore:filesize":763,"dvcore:storageIdentifier":"S3://uit-dataverseno-prod01:19d9151e17e-b734420633b1","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"3241b0e1a0abe04f45412fab1ea1100e"}},{"schema:description":"This file contains centred-log ratio (clr) values for Iron (Fe) standardised to z-scores per unit and subunit to account for sedimentological and geochemical differences across units (Toonen et al., 2015). We also provide the smoothed clr Fe signal, obtained with a 30-yr moving average in PAST v. 4 (Hammer et al., 2001).","schema:name":"Stach_2026_Fig_7_discussion_figure.txt","dvcore:restricted":false,"dvcore:directoryLabel":"8","schema:version":3,"dvcore:datasetVersionId":5646,"@id":"doi:10.18710/K3CDJJ/LZUEAC","schema:sameAs":"https://dataverse.no/api/access/datafile/:persistentId?persistentId=doi:10.18710/K3CDJJ/LZUEAC","@type":"ore:AggregatedResource","schema:fileFormat":"text/plain","dvcore:filesize":63137,"dvcore:storageIdentifier":"S3://uit-dataverseno-prod01:19d916e6d32-86f1b4043816","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"ac0e7caa061941ee0573808c05bca42a"}},{"schema:description":"This file contains Spearman’s rank correlation (ρ) and cross-correlation (r) output, both performed in PAST v. 4 (Hammer et al., 2001). The graph shown in Fig. S3 was visualised in ChiPlot (acc. 2025).\n","schema:name":"Stach_2026_Fig_S3_and_Table_2_correlation.txt","dvcore:restricted":false,"dvcore:directoryLabel":"9","schema:version":4,"dvcore:datasetVersionId":5646,"@id":"doi:10.18710/K3CDJJ/2MWYU2","schema:sameAs":"https://dataverse.no/api/access/datafile/:persistentId?persistentId=doi:10.18710/K3CDJJ/2MWYU2","@type":"ore:AggregatedResource","schema:fileFormat":"text/plain","dvcore:filesize":104185,"dvcore:storageIdentifier":"S3://uit-dataverseno-prod01:19d96ca4775-746385017125","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"0f84cd602b119b4aa9eef31965ba4f35"}},{"schema:description":"This file contains the End Member Modelling Analysis (EMMA) output (Dietze et al., 2022; Paterson et al., 2015; Prins and Weltje, 1999), generated in AnalySize v. 1.2.2 in MATLAB via the non-parametric HALS-NMF algorithm (Paterson et al., 2015).","schema:name":"Stach_2026_Fig_S4_End_Member_abundance.txt","dvcore:restricted":false,"dvcore:directoryLabel":"10","schema:version":1,"dvcore:datasetVersionId":5646,"@id":"doi:10.18710/K3CDJJ/74GHGI","schema:sameAs":"https://dataverse.no/api/access/datafile/:persistentId?persistentId=doi:10.18710/K3CDJJ/74GHGI","@type":"ore:AggregatedResource","schema:fileFormat":"text/plain","dvcore:filesize":3749,"dvcore:storageIdentifier":"S3://uit-dataverseno-prod01:19d96d2de04-ca8553a3054f","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"eb62e6e939363e4d99f5af0c6e29fe59"}},{"schema:description":"This file contains high-resolution data (0.02 cm) obtained by X-Ray fluorescence (XRF) and provides a comparison of non-detrital and detrital Iron (Fe) variability (Bertrand et al., 2024; Davies et al., 2015).","schema:name":"Stach_2026_Fig_S5_detrital_vs_redox_Fe.txt","dvcore:restricted":false,"dvcore:directoryLabel":"11","schema:version":1,"dvcore:datasetVersionId":5646,"@id":"doi:10.18710/K3CDJJ/DDZMMR","schema:sameAs":"https://dataverse.no/api/access/datafile/:persistentId?persistentId=doi:10.18710/K3CDJJ/DDZMMR","@type":"ore:AggregatedResource","schema:fileFormat":"text/plain","dvcore:filesize":268420,"dvcore:storageIdentifier":"S3://uit-dataverseno-prod01:19d9b1e0eba-583b40737b04","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"b049626b4765522619836f052166e249"}},{"schema:description":"This file contains Energy-Dispersive X-ray Spectroscopy (SEM-EDS) output, used to map and quantify elemental compositions of individual dolerite grains in Catchment Sample (CS) 1 at the grain level (Newbury and Ritchie, 2015).","schema:name":"Stach_2026_Fig_S6_SEM_EDS_detrital_carbonates_CS1.txt","dvcore:restricted":false,"dvcore:directoryLabel":"12","schema:version":3,"dvcore:datasetVersionId":5646,"@id":"doi:10.18710/K3CDJJ/LCK80E","schema:sameAs":"https://dataverse.no/api/access/datafile/:persistentId?persistentId=doi:10.18710/K3CDJJ/LCK80E","@type":"ore:AggregatedResource","schema:fileFormat":"text/plain","dvcore:filesize":48245,"dvcore:storageIdentifier":"S3://uit-dataverseno-prod01:19d9b3ad566-e387f366062f","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"21a1027637c87e831b3b09ac765330d9"}},{"schema:description":"This file contains centred-log ratio (clr) values for Iron (Fe) standardised to z-scores per unit and subunit to account for sedimentological and geochemical differences across units (Toonen et al., 2015). Phases of intensified eolian activity are recognised as values at or above the 90th percentile (p90) threshold (Hobday et al., 2016; Perkins-Kirkpatrick and Lewis, 2020), calculated separately for each unit or subunit, accounting for unit- and subunit-specific backgrounds, and highlighted in the figure by a stripped purple line.","schema:name":"Stach_2026_Fig_S7_p90_values_for_Westerly_maxima.txt","dvcore:restricted":false,"dvcore:directoryLabel":"13","schema:version":2,"dvcore:datasetVersionId":5646,"@id":"doi:10.18710/K3CDJJ/0V96Z6","schema:sameAs":"https://dataverse.no/api/access/datafile/:persistentId?persistentId=doi:10.18710/K3CDJJ/0V96Z6","@type":"ore:AggregatedResource","schema:fileFormat":"text/plain","dvcore:filesize":38824,"dvcore:storageIdentifier":"S3://uit-dataverseno-prod01:19d9b594f21-0ee985dc9ded","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"858f377be51affef89ec397725a19b3a"}},{"schema:description":"This file contains chronological data for the ~120.5 cm-long DST-2023-GC record, based on seven Accelerator Mass Spectrometry (AMS) radiocarbon (14C) dates. 14C ages were calibrated using the IntCal20 Northern Hemisphere calibration curve in RBacon v. 3.3.1 (Blaauw et al., 2022; Reimer et al., 2020), and reported within a 2σ (95%) confidence range (cal. yrs B.P.).","schema:name":"Stach_2026_Table_1_chronology.txt","dvcore:restricted":false,"dvcore:directoryLabel":"14","schema:version":3,"dvcore:datasetVersionId":5646,"@id":"doi:10.18710/K3CDJJ/MU389L","schema:sameAs":"https://dataverse.no/api/access/datafile/:persistentId?persistentId=doi:10.18710/K3CDJJ/MU389L","@type":"ore:AggregatedResource","schema:fileFormat":"text/plain","dvcore:filesize":742,"dvcore:storageIdentifier":"S3://uit-dataverseno-prod01:19d915bdcc9-6915b10e51f5","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"3dc8b96828d5527657bf056f0fec0111"}},{"schema:description":"This file contains Principal Component Analysis (PCA) factor loadings for Principal Components (PCs) 1-2, performed in PAST v. 4 (Hammer et al., 2001). We examined shared gradients of change among the following variables (n=121): Computed Tomography (CT) grayscale, Dry Bulk Density (DBD), Loss On Ignition (LOI), centred-log ratio of Iron (clr Fe), clr Titanium (Ti), and clr Calcium (Ca), and logarithmic (log) abundances of End Members (EMs) 1-3.","schema:name":"Stach_2026_Table_S1_PCA_loadings.txt","dvcore:restricted":false,"dvcore:directoryLabel":"15","schema:version":2,"dvcore:datasetVersionId":5646,"@id":"doi:10.18710/K3CDJJ/R1FUTV","schema:sameAs":"https://dataverse.no/api/access/datafile/:persistentId?persistentId=doi:10.18710/K3CDJJ/R1FUTV","@type":"ore:AggregatedResource","schema:fileFormat":"text/plain","dvcore:filesize":524,"dvcore:storageIdentifier":"S3://uit-dataverseno-prod01:19d9ba2efcf-f899dc6f1bb1","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"919b528cfb5a048a6d6aba013f2f591d"}},{"schema:description":"This file contains Energy-Dispersive X-ray Spectroscopy (SEM-EDS)-based elemental compositions of authigenic carbonate phases (Newbury and Ritchie, 2015), complementary to the Scanning Electron Microscope (SEM)-obtained high-resolution images presented in PANELS A-B of Figure 5 (Itamiya et al., 2019; Marshall et al, 2012; Vos et al., 2014).","schema:name":"Stach_2026_Table_S2_SEM_EDS_carbonates.txt","dvcore:restricted":false,"dvcore:directoryLabel":"16","schema:version":3,"dvcore:datasetVersionId":5646,"@id":"doi:10.18710/K3CDJJ/73EJCS","schema:sameAs":"https://dataverse.no/api/access/datafile/:persistentId?persistentId=doi:10.18710/K3CDJJ/73EJCS","@type":"ore:AggregatedResource","schema:fileFormat":"text/plain","dvcore:filesize":133,"dvcore:storageIdentifier":"S3://uit-dataverseno-prod01:19d9bb5ab1e-3fa4e953a8cd","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"42249c337140d22ece1a6b633c7c2f20"}},{"schema:description":"This file contains Energy- Dispersive X-ray Spectroscopy (SEM-EDS)-based oxide (wt%) compositions of Iron  (Fe), Titanium (Ti) and Calcium (Ca)-rich minerogenic phases (Newbury and Ritchie, 2015), complementary to the SEM-obtained high-resolution images presented in PANELS C-H of Figure 5 (Itamiya et al., 2019; Marshall et al., 2012; Vos et al., 2014). The elemental output (wt%) values were converted to oxide (wt%) values, following the recommendations of Kotov and Pälike (acc. 2025).","schema:name":"Stach_2026_Table_S3_SEM_EDS_EM2_EM3.txt","dvcore:restricted":false,"dvcore:directoryLabel":"17","schema:version":2,"dvcore:datasetVersionId":5646,"@id":"doi:10.18710/K3CDJJ/BFQZVJ","schema:sameAs":"https://dataverse.no/api/access/datafile/:persistentId?persistentId=doi:10.18710/K3CDJJ/BFQZVJ","@type":"ore:AggregatedResource","schema:fileFormat":"text/plain","dvcore:filesize":665,"dvcore:storageIdentifier":"S3://uit-dataverseno-prod01:19d9bc877bd-7751f33d9000","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"459f6ab05c6e46fa2d087d3b87c6ca24"}},{"schema:description":"This file contains additional Energy- Dispersive X-ray Spectroscopy (SEM-EDS)-based oxide (wt%) compositions of Iron  (Fe), Titanium (Ti) and Calcium (Ca)-rich minerogenic phases (Newbury and Ritchie, 2015), which were not presented in the study. The elemental output (wt%) values were converted to oxide (wt%) values, following the recommendations of Kotov and Pälike (acc. 2025).","schema:name":"Stach_2026_Table_S4_SEM_EDS_additional_for_EM3.txt","dvcore:restricted":false,"dvcore:directoryLabel":"18","schema:version":2,"dvcore:datasetVersionId":5646,"@id":"doi:10.18710/K3CDJJ/JT9G07","schema:sameAs":"https://dataverse.no/api/access/datafile/:persistentId?persistentId=doi:10.18710/K3CDJJ/JT9G07","@type":"ore:AggregatedResource","schema:fileFormat":"text/plain","dvcore:filesize":562,"dvcore:storageIdentifier":"S3://uit-dataverseno-prod01:19d9bdefac7-61171be253cc","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"fb237d8b7a659219660d8ba142a1f997"}},{"schema:description":"This file contains the hypsometry of mapped dolerite outcrops at Gåsøyane, Gipshuksletta, and Kapp Thorsden, derived from ArcticDEM at 2 m resolution in QGIS v. 3.34 (Nyall et al., 2026; Porter et al., 2023).","schema:name":"Stach_2026_Table_S5_dolerites_hypsometry.txt","dvcore:restricted":false,"dvcore:directoryLabel":"19","schema:version":3,"dvcore:datasetVersionId":5646,"@id":"doi:10.18710/K3CDJJ/LXOW57","schema:sameAs":"https://dataverse.no/api/access/datafile/:persistentId?persistentId=doi:10.18710/K3CDJJ/LXOW57","@type":"ore:AggregatedResource","schema:fileFormat":"text/plain","dvcore:filesize":691,"dvcore:storageIdentifier":"S3://uit-dataverseno-prod01:19d918fdc8a-ec086d61279a","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"550b66dce88ccd53c91ecc1f0f86c01b"}}],"schema:hasPart":["doi:10.18710/K3CDJJ/GJ7E4K","doi:10.18710/K3CDJJ/VA0DEN","doi:10.18710/K3CDJJ/GI7XDN","doi:10.18710/K3CDJJ/EMCF76","doi:10.18710/K3CDJJ/15XTLL","doi:10.18710/K3CDJJ/W4GC2W","doi:10.18710/K3CDJJ/KBHTBX","doi:10.18710/K3CDJJ/LZUEAC","doi:10.18710/K3CDJJ/2MWYU2","doi:10.18710/K3CDJJ/74GHGI","doi:10.18710/K3CDJJ/DDZMMR","doi:10.18710/K3CDJJ/LCK80E","doi:10.18710/K3CDJJ/0V96Z6","doi:10.18710/K3CDJJ/MU389L","doi:10.18710/K3CDJJ/R1FUTV","doi:10.18710/K3CDJJ/73EJCS","doi:10.18710/K3CDJJ/BFQZVJ","doi:10.18710/K3CDJJ/JT9G07","doi:10.18710/K3CDJJ/LXOW57"]},"@context":{"author":"http://purl.org/dc/terms/creator","authorIdentifier":"http://purl.org/spar/datacite/AgentIdentifier","authorIdentifierScheme":"http://purl.org/spar/datacite/AgentIdentifierScheme","citation":"https://dataverse.org/schema/citation/","content":"@value","dateOfDeposit":"http://purl.org/dc/terms/dateSubmitted","dcterms":"http://purl.org/dc/terms/","dvcore":"https://dataverse.org/schema/core#","geospatial":"https://dataverse.no/schema/geospatial#","grantNumber":"https://schema.org/sponsor","lang":"@language","ore":"http://www.openarchives.org/ore/terms/","otherReferences":"http://purl.org/dc/terms/references","personName":"https://schema.org/name","publication":"http://purl.org/dc/terms/isReferencedBy","publicationIDType":"http://purl.org/spar/datacite/ResourceIdentifierScheme","publicationURL":"https://schema.org/distribution","schema":"http://schema.org/","scheme":"http://www.w3.org/2004/02/skos/core#inScheme","software":"https://www.w3.org/TR/prov-o/#wasGeneratedBy","subject":"http://purl.org/dc/terms/subject","termName":"https://schema.org/name","title":"http://purl.org/dc/terms/title"}}