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Predicting provenance of forensic soil samples: Linking soil to ecological habitats by metabarcoding and supervised classification

Environmental DNA (eDNA) is increasingly applied in ecological studies, including studies with the primary purpose of criminal investigation, in which eDNA from soil can be used to pair samples or reveal sample provenance. We collected soil eDNA samples as part of a large national biodiversity resea...

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Autores principales: Fløjgaard, Camilla, Frøslev, Tobias Guldberg, Brunbjerg, Ane Kirstine, Bruun, Hans Henrik, Moeslund, Jesper, Hansen, Anders Johannes, Ejrnæs, Rasmus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6613677/
https://www.ncbi.nlm.nih.gov/pubmed/31283764
http://dx.doi.org/10.1371/journal.pone.0202844
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author Fløjgaard, Camilla
Frøslev, Tobias Guldberg
Brunbjerg, Ane Kirstine
Bruun, Hans Henrik
Moeslund, Jesper
Hansen, Anders Johannes
Ejrnæs, Rasmus
author_facet Fløjgaard, Camilla
Frøslev, Tobias Guldberg
Brunbjerg, Ane Kirstine
Bruun, Hans Henrik
Moeslund, Jesper
Hansen, Anders Johannes
Ejrnæs, Rasmus
author_sort Fløjgaard, Camilla
collection PubMed
description Environmental DNA (eDNA) is increasingly applied in ecological studies, including studies with the primary purpose of criminal investigation, in which eDNA from soil can be used to pair samples or reveal sample provenance. We collected soil eDNA samples as part of a large national biodiversity research project across 130 sites in Denmark. We investigated the potential for soil eDNA metabarcoding in predicting provenance in terms of environmental conditions, habitat type and geographic regions. We used linear regression for predicting environmental gradients of light, soil moisture, pH and nutrient status (represented by Ellenberg Indicator Values, EIVs) and Quadratic Discriminant Analysis (QDA) to predict habitat type and geographic region. eDNA data performed relatively well as a predictor of environmental gradients (R(2) > 0.81). Its ability to discriminate between habitat types was variable, with high accuracy for certain forest types and low accuracy for heathland, which was poorly predicted. Geographic region was also less accurately predicted by eDNA. We demonstrated the application of provenance prediction in forensic science by evaluating and discussing two mock crime scenes. Here, we listed the plant species from annotated sequences, which can further aid in identifying the likely habitat or, in case of rare species, a geographic region. Predictions of environmental gradients and habitat types together give an overall accurate description of a crime scene, but care should be taken when interpreting annotated sequences, e.g. due to erroneous assignments in GenBank. Our approach demonstrates that important habitat properties can be derived from soil eDNA, and exemplifies a range of potential applications of eDNA in forensic ecology.
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spelling pubmed-66136772019-07-23 Predicting provenance of forensic soil samples: Linking soil to ecological habitats by metabarcoding and supervised classification Fløjgaard, Camilla Frøslev, Tobias Guldberg Brunbjerg, Ane Kirstine Bruun, Hans Henrik Moeslund, Jesper Hansen, Anders Johannes Ejrnæs, Rasmus PLoS One Research Article Environmental DNA (eDNA) is increasingly applied in ecological studies, including studies with the primary purpose of criminal investigation, in which eDNA from soil can be used to pair samples or reveal sample provenance. We collected soil eDNA samples as part of a large national biodiversity research project across 130 sites in Denmark. We investigated the potential for soil eDNA metabarcoding in predicting provenance in terms of environmental conditions, habitat type and geographic regions. We used linear regression for predicting environmental gradients of light, soil moisture, pH and nutrient status (represented by Ellenberg Indicator Values, EIVs) and Quadratic Discriminant Analysis (QDA) to predict habitat type and geographic region. eDNA data performed relatively well as a predictor of environmental gradients (R(2) > 0.81). Its ability to discriminate between habitat types was variable, with high accuracy for certain forest types and low accuracy for heathland, which was poorly predicted. Geographic region was also less accurately predicted by eDNA. We demonstrated the application of provenance prediction in forensic science by evaluating and discussing two mock crime scenes. Here, we listed the plant species from annotated sequences, which can further aid in identifying the likely habitat or, in case of rare species, a geographic region. Predictions of environmental gradients and habitat types together give an overall accurate description of a crime scene, but care should be taken when interpreting annotated sequences, e.g. due to erroneous assignments in GenBank. Our approach demonstrates that important habitat properties can be derived from soil eDNA, and exemplifies a range of potential applications of eDNA in forensic ecology. Public Library of Science 2019-07-08 /pmc/articles/PMC6613677/ /pubmed/31283764 http://dx.doi.org/10.1371/journal.pone.0202844 Text en © 2019 Fløjgaard et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Fløjgaard, Camilla
Frøslev, Tobias Guldberg
Brunbjerg, Ane Kirstine
Bruun, Hans Henrik
Moeslund, Jesper
Hansen, Anders Johannes
Ejrnæs, Rasmus
Predicting provenance of forensic soil samples: Linking soil to ecological habitats by metabarcoding and supervised classification
title Predicting provenance of forensic soil samples: Linking soil to ecological habitats by metabarcoding and supervised classification
title_full Predicting provenance of forensic soil samples: Linking soil to ecological habitats by metabarcoding and supervised classification
title_fullStr Predicting provenance of forensic soil samples: Linking soil to ecological habitats by metabarcoding and supervised classification
title_full_unstemmed Predicting provenance of forensic soil samples: Linking soil to ecological habitats by metabarcoding and supervised classification
title_short Predicting provenance of forensic soil samples: Linking soil to ecological habitats by metabarcoding and supervised classification
title_sort predicting provenance of forensic soil samples: linking soil to ecological habitats by metabarcoding and supervised classification
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6613677/
https://www.ncbi.nlm.nih.gov/pubmed/31283764
http://dx.doi.org/10.1371/journal.pone.0202844
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