DNA barcode data reveal biogeographic trends in Arctic non-biting midges
Chironomid flies (non-biting midges) are among the most abundant and diverse animals in Arctic regions, but detailed analyses of species distributions and biogeographical patterns are hampered by challenging taxonomy and reliance on morphology for species-level identification. Here we take advantage...
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Online Access: | http://hdl.handle.net/11250/2591210 https://doi.org/10.1139/gen-2018-0100 |
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ftntnutrondheimi:oai:ntnuopen.ntnu.no:11250/2591210 2023-05-15T14:50:26+02:00 DNA barcode data reveal biogeographic trends in Arctic non-biting midges Ekrem, Torbjørn Stur, Elisabeth Orton, Matthew J. Adamowicz, Sarah J. 2018 http://hdl.handle.net/11250/2591210 https://doi.org/10.1139/gen-2018-0100 eng eng NRC Research Press (Canadian Science Publishing) http://www.nrcresearchpress.com/doi/10.1139/gen-2018-0100 Genome. 2018, 61 (11), 787-796. urn:issn:0831-2796 http://hdl.handle.net/11250/2591210 https://doi.org/10.1139/gen-2018-0100 cristin:1637883 787-796 61 Genome 11 Journal article Peer reviewed 2018 ftntnutrondheimi https://doi.org/10.1139/gen-2018-0100 2019-09-17T06:54:33Z Chironomid flies (non-biting midges) are among the most abundant and diverse animals in Arctic regions, but detailed analyses of species distributions and biogeographical patterns are hampered by challenging taxonomy and reliance on morphology for species-level identification. Here we take advantage of available DNA barcode data of Arctic Chironomidae in BOLD to analyse similarities in species distributions across a northern Nearctic – West Palearctic gradient. Using more than 260 000 barcodes representing 4666 BINs (Barcode Index Numbers) and 826 named species (some with interim names) from a combination of public and novel data, we show that the Greenland chironomid fauna shows affinities to both the Nearctic and the West Palearctic regions. While raw taxon counts indicate a strong Greenland – North American affinity, comparisons using Chao’s dissimilarity metric support a slightly higher similarity between Greenland and West Palearctic chironomid communities. Results were relatively consistent across different definitions of species taxonomic units, including morphologically determined species, BINs, and superBINs based on a ∼4.5% threshold. While most taxa found in Greenland are shared with at least one other region, reflecting circum-Arctic dispersal, our results also reveal that Greenland harbours a small endemic biodiversity. Our exploratory study showcases how DNA barcoding efforts using standardized gene regions contribute to an understanding of broad-scale patterns in biogeography by enabling joint analysis of public DNA sequence data derived from diverse prior studies. publishedVersion Copyright remains with the author(s) or their institution(s). Article in Journal/Newspaper Arctic Greenland NTNU Open Archive (Norwegian University of Science and Technology) Arctic Greenland Genome 61 11 787 796 |
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Open Polar |
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NTNU Open Archive (Norwegian University of Science and Technology) |
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ftntnutrondheimi |
language |
English |
description |
Chironomid flies (non-biting midges) are among the most abundant and diverse animals in Arctic regions, but detailed analyses of species distributions and biogeographical patterns are hampered by challenging taxonomy and reliance on morphology for species-level identification. Here we take advantage of available DNA barcode data of Arctic Chironomidae in BOLD to analyse similarities in species distributions across a northern Nearctic – West Palearctic gradient. Using more than 260 000 barcodes representing 4666 BINs (Barcode Index Numbers) and 826 named species (some with interim names) from a combination of public and novel data, we show that the Greenland chironomid fauna shows affinities to both the Nearctic and the West Palearctic regions. While raw taxon counts indicate a strong Greenland – North American affinity, comparisons using Chao’s dissimilarity metric support a slightly higher similarity between Greenland and West Palearctic chironomid communities. Results were relatively consistent across different definitions of species taxonomic units, including morphologically determined species, BINs, and superBINs based on a ∼4.5% threshold. While most taxa found in Greenland are shared with at least one other region, reflecting circum-Arctic dispersal, our results also reveal that Greenland harbours a small endemic biodiversity. Our exploratory study showcases how DNA barcoding efforts using standardized gene regions contribute to an understanding of broad-scale patterns in biogeography by enabling joint analysis of public DNA sequence data derived from diverse prior studies. publishedVersion Copyright remains with the author(s) or their institution(s). |
format |
Article in Journal/Newspaper |
author |
Ekrem, Torbjørn Stur, Elisabeth Orton, Matthew J. Adamowicz, Sarah J. |
spellingShingle |
Ekrem, Torbjørn Stur, Elisabeth Orton, Matthew J. Adamowicz, Sarah J. DNA barcode data reveal biogeographic trends in Arctic non-biting midges |
author_facet |
Ekrem, Torbjørn Stur, Elisabeth Orton, Matthew J. Adamowicz, Sarah J. |
author_sort |
Ekrem, Torbjørn |
title |
DNA barcode data reveal biogeographic trends in Arctic non-biting midges |
title_short |
DNA barcode data reveal biogeographic trends in Arctic non-biting midges |
title_full |
DNA barcode data reveal biogeographic trends in Arctic non-biting midges |
title_fullStr |
DNA barcode data reveal biogeographic trends in Arctic non-biting midges |
title_full_unstemmed |
DNA barcode data reveal biogeographic trends in Arctic non-biting midges |
title_sort |
dna barcode data reveal biogeographic trends in arctic non-biting midges |
publisher |
NRC Research Press (Canadian Science Publishing) |
publishDate |
2018 |
url |
http://hdl.handle.net/11250/2591210 https://doi.org/10.1139/gen-2018-0100 |
geographic |
Arctic Greenland |
geographic_facet |
Arctic Greenland |
genre |
Arctic Greenland |
genre_facet |
Arctic Greenland |
op_source |
787-796 61 Genome 11 |
op_relation |
http://www.nrcresearchpress.com/doi/10.1139/gen-2018-0100 Genome. 2018, 61 (11), 787-796. urn:issn:0831-2796 http://hdl.handle.net/11250/2591210 https://doi.org/10.1139/gen-2018-0100 cristin:1637883 |
op_doi |
https://doi.org/10.1139/gen-2018-0100 |
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Genome |
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61 |
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11 |
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787 |
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796 |
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1766321463704420352 |