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TitleLacustrine Arcellinina (Testate Amoebae) as bioindicators of arsenic contamination
AuthorNasser, N A; Patterson, R T; Roe, H M; Galloway, J M; Falck, H; Palmer, M J; Spence, C; Sanei, H; Macumber, A L; Neville, L A
SourceMicrobial Ecology vol. 72, issue 1, 2016 p. 130-149,
Alt SeriesEarth Sciences Sector, Contribution Series 20150355
PublisherSpringer Nature
Mediapaper; on-line; digital
File formatpdf
ProvinceNorthwest Territories
NTS85I/04; 85I/05; 85I/12; 85J/01; 85J/02; 85J/07; 85J/08; 85J/09; 85J/10
AreaYellowknife; Great Slave Lake
Lat/Long WENS-114.8500 -113.9167 62.7167 62.2333
Subjectsenvironmental geology; paleontology; surficial geology/geomorphology; geochemistry; Economics and Industry; mathematical and computational geology; surface waters; lakes; mining; mineral processing; gold; pollutants; arsenic; micropaleontology; microfossils; benthos; lake sediment geochemistry; sediment geochemistry; statistical analyses; cluster analyses; microfaunal assemblages; lake water geochemistry; atmospheric geochemistry; environmental controls; grain size analyses; pyrolysis; ecosystems; planning; Arcellinina; Testate Amoebae; lacustrine sediments; methodology; bioindicators; contamination; detrended correspondence analysis; redundancy analysis; environmental stress; bioavailability; remediation; rock-eval analyses; environmental impact; anthropogenic sources; policy
Illustrationslocation maps; rose diagrams; photomicrographs; diagrams; plots; pie charts
ProgramEnvironmental Geoscience, Tools for environmental impacts and adaptation for metal mining
Released2016 03 30
AbstractArcellininids (testate amoebae) were examined from 61 surface sediment samples collected from 59 lakes in the vicinity of former gold mines, notably Giant Mine, near Yellowknife, Northwest Territories, Canada to determine their utility as bioindicators of arsenic (As), which occurs both as a by-product of gold extraction at mines in the area and ore-bearing outcrops. Cluster analysis (Q-R-mode) and detrended correspondence analysis (DCA) reveal five arcellininid assemblages, three of which are related to varying As concentrations in the sediment samples. Redundancy analysis (RDA) showed that 14 statistically significant environmental parameters explained 57 % of the variation in faunal distribution, while partial RDA indicated that As had the greatest influence on assemblage variance (10.7 %; p < 0.10). Stress-indicating species (primarily centropyxids) characterized the faunas of samples with high As concentrations (median = 121. 7 ppm, max > 10000 ppm, min = 16.1 ppm, n = 32), while difflugiid dominated assemblages were prevalent in substrates with relatively low As concentrations (median = 30.2 ppm, max = 905.2 ppm, min = 6.3 ppm, n = 20). Most of the lakes with very high As levels are located downwind (N and W) of the former Giant Mine roaster stack where refractory ore was roasted and substantial quantities of As were released (as As2O3) to the atmosphere in the first decade of mining. This spatial pattern suggests that a significant proportion of the observed As, in at least these lakes, are industrially derived. The results of this study highlight the sensitivity of Arcellinina to As and confirm that the group has considerable potential for assessing the impact of As contamination on lakes.
Summary(Plain Language Summary, not published)
Single celled organisms (arcellaceans) from low in the food chain of lakes and wetlands were examined in sediments from lakes surrounding the former gold mine, Giant Mine, near the city of Yellowknife, Northwest Territories, Canada. It was found that arsenic concentrations in the study lakes may be causing stress in the arcellacean population and therefore may be negatively influencing the entire aquatic ecosystem. The results of this preliminary study provide new insight into the sensitivity of arcellaceans to arsenic and confirm that they hold considerable potential for assessing the impact of As contamination on lakes, which will be of value to policy makers and planners responsible for long-term monitoring of water and sediment quality in mine-impacted regions, and for informing remediation initiatives.