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

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 paper 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(K-d) presents a potential opportunity to estimate concentration ratios using K-d values. An alternative approach to the CRwo-media model proposed for estimating the transfer of radionuclides to freshwater fish is 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. Although some of the approaches considered require further development and testing, we demonstrate the potential to significantly improve predictions of radionuclide transfer to wildlife by making better use of available data. (C) 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license.