
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 (2015), Application of a Bayesian nonparametric model to derive toxicity estimates based on the response of Antarctic microbial communities to fuel-contaminated soil, Ecology and Evolution, 5, 13, p. 2633-2645. 10.1002/ece3.1493
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Article accepté pour publication ou publiéExternal document link
http://dx.doi.org/10.1002/ece3.1493Date
2015Journal name
Ecology and EvolutionVolume
5Number
13Publisher
Wiley
Pages
2633-2645
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Show full item recordAuthor(s)
Arbel, Julyan
CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
King, Catherine K.
Raymond, Ben
Winsley, Tristrom
Mengersen, Kerrie
School of Mathematical Sciences [Brisbane]
Abstract (EN)
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.Subjects / Keywords
Antarctica; dependent models; Fuel spills; Griffiths–Engen–McCloskey distribution; Shannon diversity index; soil biodiversity; species abundanceRelated items
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