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Evaluating summarised radionuclide concentration ratio datasets for wildlife.

M D Wood¹, N A Beresford, B J Howard

¹School of Environment and Life Sciences, University of Salford, Manchester M5 4WT, UK.

Journal of Environmental Radioactivity

|October 5, 2013

Summary

Radioecological models use concentration ratios (CR(wo-media)) to predict radionuclide levels in wildlife. A new statistical method reconstructs datasets to calculate condition-specific CR(wo-media) values, improving model accuracy.

Keywords:

Environmental assessment Geometric statistic Lognormal distribution Model parameter Radionuclide transfer Statistical analysis

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Area of Science:

Radioecology
Environmental Science
Wildlife Toxicology

Background:

Concentration ratios (CR(wo-media)) are crucial for radioecological models predicting radionuclide transfer from environment to wildlife.
Current generic CR(wo-media) values lead to significant discrepancies between model predictions and real-world measurements.
Existing wildlife transfer databases often contain summarized data, hindering the development of more precise, condition-specific values.

Purpose of the Study:

To develop a statistically robust method for reconstructing underlying datasets from summarized data.
To enable the calculation of condition-specific CR(wo-media) values and derive appropriate geometric summary statistics.
To improve the accuracy and reliability of radioecological models for wildlife.

Main Methods:

A novel statistical approach was developed to reconstruct detailed datasets from aggregated data.
Geometric summary statistics were employed, acknowledging the lognormal distribution of CR(wo-media) values.
The method was applied to terrestrial datasets within the Wildlife Transfer Database (WTD).

Main Results:

The study successfully reconstructed underlying datasets and calculated condition-specific CR(wo-media) values.
Statistically significant differences were found in CR(wo-media) values across sub-categories (e.g., by feeding strategy in mammals).
Dataset limitations and biases within the WTD were identified as factors influencing these differences.

Conclusions:

The developed method provides a statistically defensible way to derive condition-specific CR(wo-media) values from summarized data.
Identified sub-category differences may enhance specific radioecological assessments, but require careful interpretation due to data limitations.
The use of CR(wo-media) for estimating transfer should be approached with caution in assessments beyond the screening level due to inherent uncertainties.