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dc.contributor.authorMintram, KS
dc.contributor.authorBrown, AR
dc.contributor.authorMaynard, SK
dc.contributor.authorThorbek, P
dc.contributor.authorTyler, CR
dc.date.accessioned2018-12-17T12:36:52Z
dc.date.issued2017-09-20
dc.description.abstractEndocrine active chemicals (EACs) are widespread in freshwater environments and both laboratory and field based studies have shown reproductive effects in fish at environmentally relevant exposures. Environmental risk assessment (ERA) seeks to protect wildlife populations and prospective assessments rely on extrapolation from individual-level effects established for laboratory fish species to populations of wild fish using arbitrary safety factors. Population susceptibility to chemical effects, however, depends on exposure risk, physiological susceptibility, and population resilience, each of which can differ widely between fish species. Population models have significant potential to address these shortfalls and to include individual variability relating to life-history traits, demographic and density-dependent vital rates, and behaviors which arise from inter-organism and organism–environment interactions. Confidence in population models has recently resulted in the EU Commission stating that results derived from reliable models may be considered when assessing the relevance of adverse effects of EACs at the population level. This review critically assesses the potential risks posed by EACs for fish populations, considers the ecological factors influencing these risks and explores the benefits and challenges of applying population modeling (including individual-based modeling) in ERA for EACs in fish. We conclude that population modeling offers a way forward for incorporating greater environmental relevance in assessing the risks of EACs for fishes and for identifying key risk factors through sensitivity analysis. Individual-based models (IBMs) allow for the incorporation of physiological and behavioral endpoints relevant to EAC exposure effects, thus capturing both direct and indirect population-level effects.en_GB
dc.description.sponsorshipSyngenta Ltden_GB
dc.identifier.citationVol. 48 (2), pp. 109 - 120en_GB
dc.identifier.doi10.1080/10408444.2017.1367756
dc.identifier.grantnumberBB/M503423/1en_GB
dc.identifier.urihttp://hdl.handle.net/10871/35179
dc.language.isoenen_GB
dc.publisherTaylor & Francisen_GB
dc.rights© 2017 Informa UK Limited, trading as Taylor & Francis Group.en_GB
dc.subjectEnvironmental risk assessmenten_GB
dc.subjectendocrine active chemicalsen_GB
dc.subjectpopulation sensitivityen_GB
dc.subjectpopulation resilienceen_GB
dc.subjectlife-history strategyen_GB
dc.subjectdensity dependenceen_GB
dc.subjectpopulation modelsen_GB
dc.subjectindividual-based modelsen_GB
dc.titleCapturing ecology in modeling approaches applied to environmental risk assessment of endocrine active chemicals in fishen_GB
dc.typeArticleen_GB
dc.date.available2018-12-17T12:36:52Z
dc.identifier.issn1040-8444
dc.descriptionThis is the author accepted manuscript. The final version is available from Taylor & Francis via the DOI in this recorden_GB
dc.identifier.journalCritical Reviews in Toxicologyen_GB
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserveden_GB
dcterms.dateAccepted2017-08-11
exeter.funder::Syngenta Ltden_GB
rioxxterms.versionAMen_GB
rioxxterms.licenseref.startdate2018-02-07
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2018-12-17T12:33:29Z
refterms.versionFCDAM
refterms.dateFOA2018-12-17T12:36:59Z
refterms.panelAen_GB


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