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Detecting flying insects using car nets and DNA metabarcoding
Monitoring insects across space and time is challenging, due to their vast taxonomic and functional diversity. This study demonstrates how nets mounted on rooftops of cars (car nets) and DNA metabarcoding can be applied to sample flying insect richness and diversity across large spatial scales withi...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8086955/ https://www.ncbi.nlm.nih.gov/pubmed/33784872 http://dx.doi.org/10.1098/rsbl.2020.0833 |
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author | Svenningsen, Cecilie S. Frøslev, Tobias Guldberg Bladt, Jesper Pedersen, Lene Bruhn Larsen, Jonas Colling Ejrnæs, Rasmus Fløjgaard, Camilla Hansen, Anders Johannes Heilmann-Clausen, Jacob Dunn, Robert R. Tøttrup, Anders P. |
author_facet | Svenningsen, Cecilie S. Frøslev, Tobias Guldberg Bladt, Jesper Pedersen, Lene Bruhn Larsen, Jonas Colling Ejrnæs, Rasmus Fløjgaard, Camilla Hansen, Anders Johannes Heilmann-Clausen, Jacob Dunn, Robert R. Tøttrup, Anders P. |
author_sort | Svenningsen, Cecilie S. |
collection | PubMed |
description | Monitoring insects across space and time is challenging, due to their vast taxonomic and functional diversity. This study demonstrates how nets mounted on rooftops of cars (car nets) and DNA metabarcoding can be applied to sample flying insect richness and diversity across large spatial scales within a limited time period. During June 2018, 365 car net samples were collected by 151 volunteers during two daily time intervals on 218 routes in Denmark. Insect bulk samples were processed with a DNA metabarcoding protocol to estimate taxonomic composition, and the results were compared to known flying insect richness and occurrence data. Insect and hoverfly richness and diversity were assessed across biogeographic regions and dominant land cover types. We detected 15 out of 19 flying insect orders present in Denmark, with high proportions of especially Diptera compared to Danish estimates, and lower insect richness and diversity in urbanized areas. We detected 319 species not known for Denmark and 174 species assessed in the Danish Red List. Our results indicate that the methodology can assess the flying insect fauna at large spatial scales to a wide extent, but may be, like other methods, biased towards certain insect orders. |
format | Online Article Text |
id | pubmed-8086955 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-80869552021-05-18 Detecting flying insects using car nets and DNA metabarcoding Svenningsen, Cecilie S. Frøslev, Tobias Guldberg Bladt, Jesper Pedersen, Lene Bruhn Larsen, Jonas Colling Ejrnæs, Rasmus Fløjgaard, Camilla Hansen, Anders Johannes Heilmann-Clausen, Jacob Dunn, Robert R. Tøttrup, Anders P. Biol Lett Community Ecology Monitoring insects across space and time is challenging, due to their vast taxonomic and functional diversity. This study demonstrates how nets mounted on rooftops of cars (car nets) and DNA metabarcoding can be applied to sample flying insect richness and diversity across large spatial scales within a limited time period. During June 2018, 365 car net samples were collected by 151 volunteers during two daily time intervals on 218 routes in Denmark. Insect bulk samples were processed with a DNA metabarcoding protocol to estimate taxonomic composition, and the results were compared to known flying insect richness and occurrence data. Insect and hoverfly richness and diversity were assessed across biogeographic regions and dominant land cover types. We detected 15 out of 19 flying insect orders present in Denmark, with high proportions of especially Diptera compared to Danish estimates, and lower insect richness and diversity in urbanized areas. We detected 319 species not known for Denmark and 174 species assessed in the Danish Red List. Our results indicate that the methodology can assess the flying insect fauna at large spatial scales to a wide extent, but may be, like other methods, biased towards certain insect orders. The Royal Society 2021-03-31 /pmc/articles/PMC8086955/ /pubmed/33784872 http://dx.doi.org/10.1098/rsbl.2020.0833 Text en © 2021 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Community Ecology Svenningsen, Cecilie S. Frøslev, Tobias Guldberg Bladt, Jesper Pedersen, Lene Bruhn Larsen, Jonas Colling Ejrnæs, Rasmus Fløjgaard, Camilla Hansen, Anders Johannes Heilmann-Clausen, Jacob Dunn, Robert R. Tøttrup, Anders P. Detecting flying insects using car nets and DNA metabarcoding |
title | Detecting flying insects using car nets and DNA metabarcoding |
title_full | Detecting flying insects using car nets and DNA metabarcoding |
title_fullStr | Detecting flying insects using car nets and DNA metabarcoding |
title_full_unstemmed | Detecting flying insects using car nets and DNA metabarcoding |
title_short | Detecting flying insects using car nets and DNA metabarcoding |
title_sort | detecting flying insects using car nets and dna metabarcoding |
topic | Community Ecology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8086955/ https://www.ncbi.nlm.nih.gov/pubmed/33784872 http://dx.doi.org/10.1098/rsbl.2020.0833 |
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