Application of a Bayesian nonparametric model to derive toxicity estimates based on the response of Antarctic microbial communities to fuel‐contaminated soil
Abstract Ecotoxicology is primarily concerned with predicting the effects of toxic substances on the biological components of the ecosystem. In remote, high latitude environments such as Antarctica, where field work is logistically difficult and expensive, and where access to adequate numbers of soi...
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crwiley:10.1002/ece3.1493 2024-09-15T17:46:19+00:00 Application of a Bayesian nonparametric model to derive toxicity estimates based on the response of Antarctic microbial communities to fuel‐contaminated soil Arbel, Julyan King, Catherine K. Raymond, Ben Winsley, Tristrom Mengersen, Kerrie L. European Research Council Australian Research Council 2015 http://dx.doi.org/10.1002/ece3.1493 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fece3.1493 https://onlinelibrary.wiley.com/doi/pdf/10.1002/ece3.1493 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ece3.1493 en eng Wiley http://creativecommons.org/licenses/by/4.0/ Ecology and Evolution volume 5, issue 13, page 2633-2645 ISSN 2045-7758 2045-7758 journal-article 2015 crwiley https://doi.org/10.1002/ece3.1493 2024-07-23T04:09:27Z Abstract Ecotoxicology is primarily concerned with predicting the effects of toxic substances on the biological components of the ecosystem. In remote, high latitude environments such as Antarctica, where field work is logistically difficult and expensive, and where access to adequate numbers of soil invertebrates is limited and response times of biota are slow, appropriate modeling tools using microbial community responses can be valuable as an alternative to traditional single‐species toxicity tests. In this study, we apply a Bayesian nonparametric model to a soil microbial data set acquired across a hydrocarbon contamination gradient at the site of a fuel spill in Antarctica. We model community change in terms of OTUs (operational taxonomic units) in response to a range of total petroleum hydrocarbon (TPH) concentrations. The Shannon diversity of the microbial community, clustering of OTUs into groups with similar behavior with respect to TPH, and effective concentration values at level x , which represent the TPH concentration that causes x % change in the community, are presented. This model is broadly applicable to other complex data sets with similar data structure and inferential requirements on the response of communities to environmental parameters and stressors. Article in Journal/Newspaper Antarc* Antarctic Antarctica Wiley Online Library Ecology and Evolution 5 13 2633 2645 |
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English |
description |
Abstract Ecotoxicology is primarily concerned with predicting the effects of toxic substances on the biological components of the ecosystem. In remote, high latitude environments such as Antarctica, where field work is logistically difficult and expensive, and where access to adequate numbers of soil invertebrates is limited and response times of biota are slow, appropriate modeling tools using microbial community responses can be valuable as an alternative to traditional single‐species toxicity tests. In this study, we apply a Bayesian nonparametric model to a soil microbial data set acquired across a hydrocarbon contamination gradient at the site of a fuel spill in Antarctica. We model community change in terms of OTUs (operational taxonomic units) in response to a range of total petroleum hydrocarbon (TPH) concentrations. The Shannon diversity of the microbial community, clustering of OTUs into groups with similar behavior with respect to TPH, and effective concentration values at level x , which represent the TPH concentration that causes x % change in the community, are presented. This model is broadly applicable to other complex data sets with similar data structure and inferential requirements on the response of communities to environmental parameters and stressors. |
author2 |
European Research Council Australian Research Council |
format |
Article in Journal/Newspaper |
author |
Arbel, Julyan King, Catherine K. Raymond, Ben Winsley, Tristrom Mengersen, Kerrie L. |
spellingShingle |
Arbel, Julyan King, Catherine K. Raymond, Ben Winsley, Tristrom Mengersen, Kerrie L. Application of a Bayesian nonparametric model to derive toxicity estimates based on the response of Antarctic microbial communities to fuel‐contaminated soil |
author_facet |
Arbel, Julyan King, Catherine K. Raymond, Ben Winsley, Tristrom Mengersen, Kerrie L. |
author_sort |
Arbel, Julyan |
title |
Application of a Bayesian nonparametric model to derive toxicity estimates based on the response of Antarctic microbial communities to fuel‐contaminated soil |
title_short |
Application of a Bayesian nonparametric model to derive toxicity estimates based on the response of Antarctic microbial communities to fuel‐contaminated soil |
title_full |
Application of a Bayesian nonparametric model to derive toxicity estimates based on the response of Antarctic microbial communities to fuel‐contaminated soil |
title_fullStr |
Application of a Bayesian nonparametric model to derive toxicity estimates based on the response of Antarctic microbial communities to fuel‐contaminated soil |
title_full_unstemmed |
Application of a Bayesian nonparametric model to derive toxicity estimates based on the response of Antarctic microbial communities to fuel‐contaminated soil |
title_sort |
application of a bayesian nonparametric model to derive toxicity estimates based on the response of antarctic microbial communities to fuel‐contaminated soil |
publisher |
Wiley |
publishDate |
2015 |
url |
http://dx.doi.org/10.1002/ece3.1493 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fece3.1493 https://onlinelibrary.wiley.com/doi/pdf/10.1002/ece3.1493 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ece3.1493 |
genre |
Antarc* Antarctic Antarctica |
genre_facet |
Antarc* Antarctic Antarctica |
op_source |
Ecology and Evolution volume 5, issue 13, page 2633-2645 ISSN 2045-7758 2045-7758 |
op_rights |
http://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.1002/ece3.1493 |
container_title |
Ecology and Evolution |
container_volume |
5 |
container_issue |
13 |
container_start_page |
2633 |
op_container_end_page |
2645 |
_version_ |
1810494362377781248 |