Individual level spatial-temporal modelling of exposure potential of livestock in the Cove Wash watershed, Arizona

Personal exposure studies suffer from uncertainty issues, largely stemming from individual behaviour uncertainties. Built on spatial-temporal exposure analysis and methods, this study proposed a novel approach to spatial-temporal modelling that incorporated behaviour classifications taking into account uncertainties, to estimate individual livestock exposure potential. The new approach was applied in a community-based research project with a Tribal community in the southwest United States to address questions on potential livestock exposure to abandoned uranium mines (AUMs). The study aimed to 1) classify Global Positioning System (GPS) data from livestock into three behaviour subgroups - grazing, travelling or resting; 2) calculate the daily cumulative exposure potential for livestock; 3) assess the performance of the computational method with and without behaviour classifications. Using Lotek Litetrack GPS collars, we collected data at a 20-min-interval for two flocks of sheep and goats during the spring and summer of 2019. Analysis and modelling of GPS data demonstrated no significant difference in individual cumulative exposure potential within each flock when animal behaviours with probability/uncertainties were considered. However, when daily cumulative exposure potential was calculated without consideration of animal behaviour or probability/uncertainties, significant differences among animals within a herd were observed, which does not match animal grazing behaviours reported by livestock owners. These results suggest that the proposed method including behaviour subgroups with probability/uncertainties more closely resembled the observed grazing behaviours. Results from the research may be used for future intervention and policy-making on remediation efforts in communities where grazing livestock may encounter environmental contaminants.