File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Power analysis for biomarkers in mussels for use in coastal pollution monitoring

TitlePower analysis for biomarkers in mussels for use in coastal pollution monitoring
Authors
KeywordsEnvironmental monitoring
Minimum detectable difference
Natural variability
Optimum sample size
Power analysis
Issue Date2009
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/marpolbul
Citation
Marine Pollution Bulletin, 2009, v. 58 n. 8, p. 1152-1158 How to Cite?
AbstractData from literature on neutral red retention time (NRRT) in lysosomes, micronucleus (MN) frequency and condition index (CI) in mussel Mytilus, especially Mytilus edulis and Mytilus galloprovincialis, were re-analyzed to ascertain their statistical power in detecting a minimum 20% spatial/temporal change in field studies. Results showed that CI largely displayed higher statistical power (>90%) than lysosomal NRRT and MN frequency (<50%), suggesting that data from the latter two biomarkers may lead to erroneous conclusions if sample size is inadequate. Samples of green-lipped mussel Perna viridis were also analyzed in Hong Kong. To achieve statistically valid power, the optimal sample sizes for monitoring lysosomal NRRT, MN frequency, CI and gonosomatic index (GSI) were determined as ≥34, ≥90, ≥16 and ≥29, respectively. Natural variability of lysosomal NRRT and MN frequency was significantly greater than CI and/or GSI in mussels, rejecting the general belief in the greater variability of higher-tiered hierarchical biomarkers. © 2009 Elsevier Ltd. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/179148
ISSN
2021 Impact Factor: 7.001
2020 SCImago Journal Rankings: 1.548
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorFang, JKHen_US
dc.contributor.authorWu, RSSen_US
dc.contributor.authorYip, CKMen_US
dc.contributor.authorShin, PKSen_US
dc.date.accessioned2012-12-19T09:52:22Z-
dc.date.available2012-12-19T09:52:22Z-
dc.date.issued2009en_US
dc.identifier.citationMarine Pollution Bulletin, 2009, v. 58 n. 8, p. 1152-1158en_US
dc.identifier.issn0025-326Xen_US
dc.identifier.urihttp://hdl.handle.net/10722/179148-
dc.description.abstractData from literature on neutral red retention time (NRRT) in lysosomes, micronucleus (MN) frequency and condition index (CI) in mussel Mytilus, especially Mytilus edulis and Mytilus galloprovincialis, were re-analyzed to ascertain their statistical power in detecting a minimum 20% spatial/temporal change in field studies. Results showed that CI largely displayed higher statistical power (>90%) than lysosomal NRRT and MN frequency (<50%), suggesting that data from the latter two biomarkers may lead to erroneous conclusions if sample size is inadequate. Samples of green-lipped mussel Perna viridis were also analyzed in Hong Kong. To achieve statistically valid power, the optimal sample sizes for monitoring lysosomal NRRT, MN frequency, CI and gonosomatic index (GSI) were determined as ≥34, ≥90, ≥16 and ≥29, respectively. Natural variability of lysosomal NRRT and MN frequency was significantly greater than CI and/or GSI in mussels, rejecting the general belief in the greater variability of higher-tiered hierarchical biomarkers. © 2009 Elsevier Ltd. All rights reserved.en_US
dc.languageengen_US
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/marpolbulen_US
dc.relation.ispartofMarine Pollution Bulletinen_US
dc.subjectEnvironmental monitoring-
dc.subjectMinimum detectable difference-
dc.subjectNatural variability-
dc.subjectOptimum sample size-
dc.subjectPower analysis-
dc.subject.meshAnimalsen_US
dc.subject.meshBiological Markers - Analysisen_US
dc.subject.meshBivalvia - Metabolismen_US
dc.subject.meshEnvironmental Monitoring - Methodsen_US
dc.subject.meshHong Kongen_US
dc.subject.meshWater Pollutants, Chemical - Analysisen_US
dc.titlePower analysis for biomarkers in mussels for use in coastal pollution monitoringen_US
dc.typeArticleen_US
dc.identifier.emailWu, RSS: rudolfwu@hku.hken_US
dc.identifier.authorityWu, RSS=rp01398en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1016/j.marpolbul.2009.04.003en_US
dc.identifier.pmid19406439-
dc.identifier.scopuseid_2-s2.0-67651108851en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-67651108851&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume58en_US
dc.identifier.issue8en_US
dc.identifier.spage1152en_US
dc.identifier.epage1158en_US
dc.identifier.isiWOS:000269142000018-
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridFang, JKH=24168119000en_US
dc.identifier.scopusauthoridWu, RSS=7402945079en_US
dc.identifier.scopusauthoridYip, CKM=7101665503en_US
dc.identifier.scopusauthoridShin, PKS=7004445653en_US
dc.identifier.citeulike5148925-
dc.identifier.issnl0025-326X-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats