Spatial trends in a biomagnifying contaminant: Application of amino acid compound–specific stable nitrogen isotope analysis to the interpretation of bird mercury levels

Abstract

Levels of biomagnifying contaminants are greatest in high-trophic level biota (e.g., predatory birds such as gulls). Gull eggs have been used to assess contaminant spatial patterns and sources, but such assessments must consider how organism trophic position may influence spatial inferences. Stable nitrogen isotopes (δ N) in bulk tissue are routinely used in this context. However, bulk δ N values are only useful if spatial differences in baseline δ N values are considered. Amino acid compound-specific stable nitrogen isotope analysis can generate estimates of baseline δ N values and trophic position from the same sample. In the present study, eggs (n = 428) of California (Larus californicus), herring (Larus argentatus smithsonianus), and ring-billed (Larus delawarensis) gulls were used to assess spatial patterns in mercury (Hg) availability in 12 western Canadian lakes located over 14 degrees of latitude, with amino acid compound-specific stable isotope analysis adjustment of egg Hg levels for trophic position. Mean trophic position-adjusted egg Hg levels (micrograms per gram, dry wt) were greatest at sites in receiving waters of the Athabasca River (X¯ = 0.70) compared to southern (X¯ = 0.39) and northern (X¯ = 0.50) regions. Research is required to investigate factors (e.g., local Hg released as a result of human activities, processes influencing Hg methylation) which may be responsible for greater Hg availability in the lower Athabasca River basin. However, it is clear that amino acid compound-specific stable isotope analysis is a valuable tool for assessing contaminant spatial patterns. Environ Toxicol Chem 2018;37:1466-1475. © 2018 SETAC.

Advances in science and applications of air pollution monitoring: A case study on oil sands monitoring targeting ecosystem protection

“…In the PAD, as elsewhere, colonial waterbirds are hightropic-level species and therefore can accumulate high levels of biomagnifying contaminants such as Hg (Dolgova et al 2018b). Colonial waterbird eggs from gull and tern colonies in downstream receiving environments of the LAR were therefore used to assess spatial and temporal trends in Hg, arsenic (As), and PACs in eggs (Campbell et al 2013;Hebert, Nordstrom, and Shutt 2010;Hebert et al 2011).…”

“…Colonial waterbird eggs from gull and tern colonies in downstream receiving environments of the LAR were therefore used to assess spatial and temporal trends in Hg, arsenic (As), and PACs in eggs (Campbell et al 2013;Hebert, Nordstrom, and Shutt 2010;Hebert et al 2011). A key methodological development enabled this assessment, namely, the ability to standardize concentrations across space and species through the use of compoundspecific amino acid stable isotope analyses (Dolgova et al 2018a(Dolgova et al , 2018b. This approach can account for different embryonic developmental stages across different colonial waterbird species at different trophic positions.…”

“…Letters above means indicate statistical differences (means with the same letter are not different). Phe = phenylalanine (Dolgova et al 2018b).…”

Geospatial analysis of the patterns of chemical exposures among biota in the Canadian Oil Sands Region

“…Annual sampling campaigns in the wildlife contaminants and toxicology monitoring program in JOSM measured a selected suite of chemical contaminants in wood frogs (Lithobates sylvaticus); fur-bearing mammals including river otter (Lontra canadensis), mink (Neovision vision), fisher (Martes pennant), and marten (Martes Americana); birds including the eggs of Caspian Terns (Hydroprogne caspia) and California Gulls (Larus californicus), and tree swallow (Tachycineta bicolor) nestlings; and a variety of aboveground and belowground plant matter. In the wildlife contaminants monitoring program, exposure to contaminants was measured in collected tissues, including liver, feathers, and eggs [8][9][10][11][12][13]. Programs under JOSM also monitored abiotic matrices, including air, water, and aerial deposition of contaminants, including in snow.…”

The Use of Geographic Information Systems for Spatial Ecological Risk Assessments: An Example from the Athabasca Oil Sands Area in Canada

“…We also provide a proof-of-concept example for demonstration purposes of how to assess the spatial co-occurrence between exposures and responses. (Hebert et al 2013;Dolgova et al 2018), plants (Boutin and Carpenter 2017), and terrestrial and semiaquatic mammals (Thomas et al 2017). Biological samples from the monitoring activity were geolocated, and tissues (and some abiotic samples) were analyzed for a variety of contaminants, including metals and PACs, and in some species, health indicators were measured, including thyroid hormones (triiodothyronine and thyroxine) and cortisol (Government of Canada 2017).…”