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Conference Paper: A Bayesian mixture model for estimating intergeneration chronic toxicity

TitleA Bayesian mixture model for estimating intergeneration chronic toxicity
Authors
KeywordsBayesian networks
Copper
Mixtures
Statistical methods
Toxicity
Issue Date2008
PublisherAmerican Chemical Society. The Journal's web site is located at http://pubs.acs.org/est
Citation
The 2010 SETAC Asia/Pacific Meeting, Guangzhou, China, 4-7 June 2010. In Environmental Science & Technology (Washington), 2008, v. 42 n. 21, p. 8108-8114 How to Cite?
AbstractUnderstanding toxic effects on biological populations across generations is crucial for determining the long-term consequences of chemical pollution in aquatic environments. As a consequence, there is considerable demand for suitable statistical methods to analyze complex multigeneration experimental data. We demonstrate the application of a Bayesian mixture model (with random-effects) to assess the effect of intergeneration copper (Cu) exposure on the reproductive output of the copepod, Tigriopus japonicus, using experimental data across three generations. The model allowed us to appropriately specify the nonstandard statistical distribution of the data and account for correlations among data points. The approach ensured more robust inferences than standard statistical methods and, because of the model's mechanistic formulation, enabled us to test more subtle hypotheses. We demonstrate intergeneration Cu exposure effects on both components of reproductive output (1) the ovisac maturation rate, and (2) the number of nauplii per ovisac. Current and parent generation Cu exposures negatively affected current generation reproductive output. However, in terms of reproductive output, there was also some evidence for adaptation to parental Cu exposures, but with an associated cost under Cu concentrations different from the parental exposure. Bayesian mixture and random-effects models present a robust framework for analyzing data of this kind and for better understanding chemical toxicity. © 2008 American Chemical Society.
Persistent Identifierhttp://hdl.handle.net/10722/130252
ISSN
2015 Impact Factor: 5.393
2015 SCImago Journal Rankings: 2.664
ISI Accession Number ID
Funding AgencyGrant Number
CSIRO
UQ
Area of Excellence Scheme
Hong Kong AR GovernmentAoE/P-04/2004
Funding Information:

J.R.R. was supported by a CSIRO Postdoctoral Fellowship and a UQ Postdoctoral Fellowship, and K.W.H.K. was partly supported by the Area of Excellence Scheme under the University Grants Committee of the Hong Kong AR Government (project no. AoE/P-04/2004).

References

 

DC FieldValueLanguage
dc.contributor.authorRhodes, JRen_HK
dc.contributor.authorGrist, EPMen_HK
dc.contributor.authorKwok, KWHen_HK
dc.contributor.authorLeung, KMYen_HK
dc.date.accessioned2010-12-23T08:48:30Z-
dc.date.available2010-12-23T08:48:30Z-
dc.date.issued2008en_HK
dc.identifier.citationThe 2010 SETAC Asia/Pacific Meeting, Guangzhou, China, 4-7 June 2010. In Environmental Science & Technology (Washington), 2008, v. 42 n. 21, p. 8108-8114en_US
dc.identifier.issn0013-936Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/130252-
dc.description.abstractUnderstanding toxic effects on biological populations across generations is crucial for determining the long-term consequences of chemical pollution in aquatic environments. As a consequence, there is considerable demand for suitable statistical methods to analyze complex multigeneration experimental data. We demonstrate the application of a Bayesian mixture model (with random-effects) to assess the effect of intergeneration copper (Cu) exposure on the reproductive output of the copepod, Tigriopus japonicus, using experimental data across three generations. The model allowed us to appropriately specify the nonstandard statistical distribution of the data and account for correlations among data points. The approach ensured more robust inferences than standard statistical methods and, because of the model's mechanistic formulation, enabled us to test more subtle hypotheses. We demonstrate intergeneration Cu exposure effects on both components of reproductive output (1) the ovisac maturation rate, and (2) the number of nauplii per ovisac. Current and parent generation Cu exposures negatively affected current generation reproductive output. However, in terms of reproductive output, there was also some evidence for adaptation to parental Cu exposures, but with an associated cost under Cu concentrations different from the parental exposure. Bayesian mixture and random-effects models present a robust framework for analyzing data of this kind and for better understanding chemical toxicity. © 2008 American Chemical Society.en_HK
dc.languageengen_US
dc.publisherAmerican Chemical Society. The Journal's web site is located at http://pubs.acs.org/esten_HK
dc.relation.ispartofEnvironmental Science and Technologyen_HK
dc.rightsThe original publication is available at www.springerlink.com-
dc.subjectBayesian networks-
dc.subjectCopper-
dc.subjectMixtures-
dc.subjectStatistical methods-
dc.subjectToxicity-
dc.titleA Bayesian mixture model for estimating intergeneration chronic toxicityen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1382-3124&volume=42&issue=21&spage=8108&epage=8114&date=2010&atitle=A+Bayesian+mixture+model+for+estimating+intergeneration+chronic+toxicity-
dc.identifier.emailLeung, KMY: kmyleung@hku.hken_HK
dc.identifier.authorityLeung, KMY=rp00733en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1021/es801030ten_HK
dc.identifier.pmid19031910-
dc.identifier.scopuseid_2-s2.0-55349138384en_HK
dc.identifier.hkuros178138en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-55349138384&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume42en_HK
dc.identifier.issue21en_HK
dc.identifier.spage8108en_HK
dc.identifier.epage8114en_HK
dc.identifier.isiWOS:000260561200063-
dc.publisher.placeUnited Statesen_HK
dc.description.otherThe 2010 SETAC Asia/Pacific Meeting, Guangzhou, China, 4-7 June 2010. In Environmental Science & Technology (Washington), 2008, v. 42 n. 21, p. 8108-8114-
dc.identifier.scopusauthoridRhodes, JR=8088323300en_HK
dc.identifier.scopusauthoridGrist, EPM=7003398590en_HK
dc.identifier.scopusauthoridKwok, KWH=19337480200en_HK
dc.identifier.scopusauthoridLeung, KMY=7401860738en_HK

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