Exploring taxonomic and phylogenetic relationships to predict radiocaesium transfer to marine biota

Abstract

One potentially useful approach to fill data gaps for concentration ratios, CRs, is based upon the hypothesis that an underlying taxonomic and/or phylogenetic relationship exists for radionuclide transfer. The objective of this study was to explore whether these relationships could be used to explain variation in the transfer of radiocaesium to a wide range of marine organisms. CR data for Cs were classified in relation to taxonomic family, order, class and phylum. A Residual Maximum Likelihood (REML) mixed-model regression modelling approach was adopted. The existence of any patterns were then explored using phylogenetic trees constructed with mitochondrial COI gene sequences from various biota groups and mapping the REML residual means onto these trees. A comparison of the predictions made using REML with blind datasets allowed the efficacy of the procedure to be tested. The only significant correlation between predicted and measured activity concentrations was revealed at the taxonomic level of order when comparing REML analysis output with data from the Barents Sea Region. For this single case a correlation 0.80 (Spearman rank) was derived which was significant at the 0.01 level (1-tailed test) although this was not the case once a (Bonferroni) correction was applied. The application of the REML approach to marine datasets has met with limited success, and the phylogenetic trees illustrate complications of using predictions based on values from different levels of taxonomic organization, where predicted values for the order level can mask the values at lower taxonomic levels. Any influence of taxonomy and phylogeny on transfer is not immediately conspicuous and categorizing marine organisms in this way is limited in providing a potentially robust prognostic extrapolation tool. Other factors may plausibly affect transfer to a much greater degree in marine systems, such as quite diverse life histories and different diets, which may confound any phylogenetic pattern.

Towards solving a scientific controversy – The effects of ionising radiation on the environment

“…The validations undertaken to date have shown the resultant transfer predictions to be closer to measured values than those obtained using the CR approach for Cs and freshwater fish (Beresford et al, 2013(Beresford et al, , 2016b, and Sr, Cs, U, Pb and Se for terrestrial species (Søvik et al, 2017;Beresford and Willey, 2019). However, whilst it was possible to apply this approach to the available data for marine species for Cs, validation against blind test datasets for a range of marine species revealed poor predictions (Brown et al, 2019); further work is required to determine the applicability of this approach to marine ecosystems.…”

Ensuring robust radiological risk assessment for wildlife: insights from the International Atomic Energy Agency EMRAS and MODARIA programmes

“…Currently, such models have been demonstrated for Cs in freshwater fish and Pb in terrestrial organisms, with Søvik et al (2017) suggesting it will be possible to establish models for a wider range of radionuclides (Cs, Sr, U and Se). However, we note that whilst the predictive power of these initial models was good for freshwater fish and terrestrial organisms, it was poor for Cs in marine organisms (Brown et al 2019).…”

“…Furthermore, to address data gaps and uncertainties in the CRwo-media approach, novel approaches to estimating the transfer of radionuclides to wildlife are being developed and tested (Beresford et al , 2016aBeresford & Wiley 2019;Beresford & Vives i Batlle 2013;Brown et al 2019;Søvik et al 2017;Vives i Batlle et al 2007b). Some new/developing assessment approaches described above differ considerably from the more established models/tools that we have tested.…”

Radiocesium accumulation in aquatic organisms: A global synthesis from an experimentalist's perspective

“…Linking taxonomy, phylogeny and radiocesium bioaccumulation can be very complex (Brown et al, 2019). Nevertheless, a simple meta-analysis of data from the database revealed differences in the CFs and AEs observed among the different kingdoms (Animalia, Bacteria, Chromista and Plantae).…”