Making the most of what we have: application of extrapolation approaches in radioecological wildlife transfer models

Nicholas Beresford, Michael Wood, Jordi Vives i Batlle, Tamara Yankovich, Clare Bradshaw, Neil Willey, Nele Horemans

    Research outputpeer-review

    Abstract

    We will never have data to populate all of the potential radioecological modelling parameters required for wildlife assessments. Therefore, we need robust extrapolation approaches which allow us to make best use of our available knowledge. This papers, reviews, and in some cases, develops, tests and validates some of the suggested extrapolation approaches. The concentration ratio (CRproduct-diet or CRwo-diet) is shown to be a generic (trans-species) parameter which should enable the more abundant data for farm animals to be applied to wild species. An allometric model for predicting the biological half-life of radionuclides in vertebrates is further tested and generally shown to perform acceptably. However, to fully exploit allometry we need to understand why some elements do not scale to expected values. For aquatic ecosystems, the relationship between log10(a) (a parameter from the allometric relationship for the organism-water concentration ratio) and log(Kd) presents a potential opportunity to estimate concentration ratio values using Kd. An alternative approach to the CRwo-media model proposed for estimating the transfer of radionuclides to freshwater fish was used to satisfactorily predict activity concentrations in fish of different species from three lakes. We recommend that this approach (REML modelling) be further investigated and developed for other radionuclides and across a wider range of organisms and ecosystems. Ecological stoichiometry shows potential as an extrapolation method in radioecology, either from one element to another or from one species to another.
    Original languageEnglish
    Pages (from-to)373-386
    Number of pages14
    JournalJournal of environmental radioactivity
    Volume151
    DOIs
    StatePublished - 1 Jan 2016

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