ArticlePloS one2020
Geospatial analysis of the patterns of chemical exposures among biota in the Canadian Oil Sands Region.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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0 citing papers in PubMed, 7 citations in OpenAlex.
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Understanding the patterns of chemical exposure among biota across a landscape is challenging due to the spatial heterogeneity and complexity of the sources, pathways, and fate of the different chemicals. While spatially-driven relationships between contaminant sources and biota body burdens of a single chemical are commonly modelled, there has been little effort on modelling chemical mixtures across multiple wildlife species in the Canadian Oil Sands region. In this study, we used spatial principal components analysis (sPCA) to assess spatial patterns of the body burdens of 22 metals and Potentially Toxic Elements (PTEs) in 492 individual wildlife, including fur-bearing mammals, colonial waterbirds, and amphibians collected from the Canadian Oil Sands region in Canada. Spatial analysis and mapping both indicate that some of the complex exposures in the studied biota are distributed randomly across a landscape, which suggests background or non-point source exposures. In contrast, the pattern of exposure for seven metals and PTEs, including mercury, vanadium, lead, rubidium, lithium, strontium, and barium, exhibited a clustered pattern to the east of the open-pit mining area and in regions downstream of oil sands development which indicates point-source input. This analysis demonstrated useful methods for integrating monitoring datasets and identifying sources and potential drivers of exposure to chemical mixtures in biota across a landscape. These results can be used to support an adaptive monitoring program by identifying regions needing additional monitoring, health impact assessments, and possible intervention strategies.
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