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A harmonized dataset of sediment diatoms from hundreds of lakes in the northeastern United States

Sediment diatoms are widely used to track environmental histories of lakes and their watersheds, but merging datasets generated by different researchers for further large-scale studies is challenging because of taxonomic discrepancies caused by rapidly evolving diatom nomenclature and taxonomic conc...

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Autores principales: Potapova, Marina G., Lee, Sylvia S., Spaulding, Sarah A., Schulte, Nicholas O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9440916/
https://www.ncbi.nlm.nih.gov/pubmed/36057654
http://dx.doi.org/10.1038/s41597-022-01661-3
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author Potapova, Marina G.
Lee, Sylvia S.
Spaulding, Sarah A.
Schulte, Nicholas O.
author_facet Potapova, Marina G.
Lee, Sylvia S.
Spaulding, Sarah A.
Schulte, Nicholas O.
author_sort Potapova, Marina G.
collection PubMed
description Sediment diatoms are widely used to track environmental histories of lakes and their watersheds, but merging datasets generated by different researchers for further large-scale studies is challenging because of taxonomic discrepancies caused by rapidly evolving diatom nomenclature and taxonomic concepts. We collated five datasets of lake sediment diatoms from the Northeastern USA using a harmonization process which included updating synonyms, tracking the identity of inconsistently identified taxa, and grouping those that could not be resolved taxonomically. Each harmonization step led to an increase in variation explained by environmental variables and a parallel reduction of variation attributable to taxonomic inconsistency. To maximize future use of the data and underlying specimens we provide the original and harmonized counts for 1327 core samples from 607 lakes, name translation schemes, sample metadata, specimen museum locations, and the Northeast Lakes Voucher Flora, which is a set of light microscope images grouped into 1154 morphological operational taxonomic units. Post-hoc harmonization enables data quality control when other approaches (e.g., upfront management of taxonomic consistency) are not possible.
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spelling pubmed-94409162022-09-05 A harmonized dataset of sediment diatoms from hundreds of lakes in the northeastern United States Potapova, Marina G. Lee, Sylvia S. Spaulding, Sarah A. Schulte, Nicholas O. Sci Data Data Descriptor Sediment diatoms are widely used to track environmental histories of lakes and their watersheds, but merging datasets generated by different researchers for further large-scale studies is challenging because of taxonomic discrepancies caused by rapidly evolving diatom nomenclature and taxonomic concepts. We collated five datasets of lake sediment diatoms from the Northeastern USA using a harmonization process which included updating synonyms, tracking the identity of inconsistently identified taxa, and grouping those that could not be resolved taxonomically. Each harmonization step led to an increase in variation explained by environmental variables and a parallel reduction of variation attributable to taxonomic inconsistency. To maximize future use of the data and underlying specimens we provide the original and harmonized counts for 1327 core samples from 607 lakes, name translation schemes, sample metadata, specimen museum locations, and the Northeast Lakes Voucher Flora, which is a set of light microscope images grouped into 1154 morphological operational taxonomic units. Post-hoc harmonization enables data quality control when other approaches (e.g., upfront management of taxonomic consistency) are not possible. Nature Publishing Group UK 2022-09-03 /pmc/articles/PMC9440916/ /pubmed/36057654 http://dx.doi.org/10.1038/s41597-022-01661-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Data Descriptor
Potapova, Marina G.
Lee, Sylvia S.
Spaulding, Sarah A.
Schulte, Nicholas O.
A harmonized dataset of sediment diatoms from hundreds of lakes in the northeastern United States
title A harmonized dataset of sediment diatoms from hundreds of lakes in the northeastern United States
title_full A harmonized dataset of sediment diatoms from hundreds of lakes in the northeastern United States
title_fullStr A harmonized dataset of sediment diatoms from hundreds of lakes in the northeastern United States
title_full_unstemmed A harmonized dataset of sediment diatoms from hundreds of lakes in the northeastern United States
title_short A harmonized dataset of sediment diatoms from hundreds of lakes in the northeastern United States
title_sort harmonized dataset of sediment diatoms from hundreds of lakes in the northeastern united states
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9440916/
https://www.ncbi.nlm.nih.gov/pubmed/36057654
http://dx.doi.org/10.1038/s41597-022-01661-3
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