Assessing the uncertainty of exposure of wildlife under field conditions
The current approaches used to estimate the exposure of wildlife to ionising radiation have been criticised as being too simplistic because they do not consider how animals utilise their environment. The ‘state-of-the-art’ is typically to average the available measurements of media concentrations or, at best, to use geographical information systems to estimate an average concentration within a typical home range for a given species. There is little evidence to support or counter the criticisms or to evaluate uncertainties associated with existing methodologies. Whilst there have been a number of international model-data comparisons, few studies have attempted to measure the exposure of wildlife to validate predictive exposure models. TREE aimed to provide an evaluation of the extent to which current simplistic and pragmatic exposure assumptions ensure that wildlife are protected.
Hypotheses
Current simplistic assumptions which ignore how animals utilise their environment ensure wildlife is protected by generating a conservative estimate of exposure.
Wildlife camera traps
Working with our Ukrainian collaborators (Chornobyl Center), we deployed 42 wildlife trap cameras within the Chornobyl exclusion zone (CEZ). We were able to use the cameras to make population estimates thereby providing a useful input to the debate on the impact of ionising radiation on wildlife in the CEZ.
Estimating the exposure of wild mammals
We evaluated pathways of exposure for large mammals. Mammals were studied due to their relatively large home ranges which enabled us to assess the often simplistic assumptions that are currently used in exposure assessments. We fitted reindeer in an area of Norway with a variety of different passive dosimeters; the reindeer also had GPS collars. The resultant data enabled us to determine the actual external dose rate received and compare this to the dose predicted using: (i) ‘the traditional approaches’ of assuming home ranges around the point of capture; (ii) spatial behaviour models and GPS tracking data.
