Norwegian Radiation Protection Authority, Grini næringspark 13, 1361 Østerås, Norway; CERAD Center of Excellence in Environmental Radioactivity, P.O. Box 5003, NO-1432 Ås, Norway.
NERC Centre for Ecology & Hydrology, UK.
Sci Total Environ. 2019 Feb 1;649:916-928. doi: 10.1016/j.scitotenv.2018.08.343. Epub 2018 Aug 28.
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.
填补浓度比(CRs)数据空白的一种潜在有用方法基于这样一种假设,即放射性核素转移存在潜在的分类学和/或系统发育关系。本研究的目的是探索这些关系是否可用于解释放射性铯向广泛的海洋生物转移的变化。将 Cs 的 CR 数据按分类家族、目、纲和门进行分类。采用残差最大似然(REML)混合模型回归建模方法。然后使用来自不同生物群的线粒体 COI 基因序列构建系统发育树,将 REML 残差均值映射到这些树上,以探索任何模式的存在。使用 REML 与盲数据集进行预测的比较允许测试该程序的效果。在与巴伦支海地区的数据进行比较时,仅在目这一分类学水平上发现了预测和测量的活性浓度之间存在显著相关性。对于这种情况,得出了 0.80(Spearman 秩)的相关性,在 0.01 水平(单侧检验)上具有统计学意义,尽管在应用(Bonferroni)校正后并非如此。REML 方法在海洋数据集上的应用取得了有限的成功,系统发育树说明了在使用来自不同分类组织水平的值进行预测时存在的复杂性,其中目水平的预测值可能掩盖了较低分类学水平的预测值。分类学和系统发育对转移的影响并不明显,以这种方式对海洋生物进行分类在提供潜在稳健的预测外推工具方面受到限制。其他因素可能在海洋系统中对转移产生更大的影响,例如非常不同的生活史和不同的饮食,这可能会使任何系统发育模式复杂化。