Department of Biology, University of Ottawa, Ottawa, ON, Canada.
Science and Technology Branch, Environment and Climate Change Canada, National Wildlife Research Center, Ottawa, ON, Canada.
PLoS One. 2020 Sep 30;15(9):e0239086. doi: 10.1371/journal.pone.0239086. eCollection 2020.
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.
由于不同化学物质的来源、途径和归宿在空间上存在异质性和复杂性,因此了解景观中生物群的化学暴露模式具有挑战性。虽然通常会对单一化学物质的污染物来源与生物群体内负荷之间的空间关系进行建模,但在加拿大油砂地区的多个野生动物物种中对化学混合物进行建模的工作却很少。在这项研究中,我们使用空间主成分分析(sPCA)来评估加拿大油砂地区采集的 492 只个体野生动物(包括有毛哺乳动物、水鸟和两栖动物)体内 22 种金属和潜在有毒元素(PTE)的体内负荷的空间分布模式。空间分析和制图均表明,研究生物群中一些复杂的暴露是随机分布在整个景观中的,这表明存在背景或非点源暴露。相比之下,七种金属和 PTE(包括汞、钒、铅、铷、锂、锶和钡)的暴露模式呈现出在露天采矿区以东以及油砂开发下游地区的集群模式,这表明存在点源输入。这项分析展示了整合监测数据集、识别景观中生物群中化学混合物的暴露源和潜在驱动因素的有用方法。这些结果可用于支持适应性监测计划,确定需要额外监测、健康影响评估和可能的干预策略的区域。