Evidence map›Paper›PMID 32411528›Full record

ArticlePeerJ2020

Intra-lake response of Arcellinida (testate lobose amoebae) to gold mining-derived arsenic contamination in northern Canada: Implications for environmental monitoring.

Nawaf A Nasser, R Timothy Patterson, Jennifer M Galloway, Hendrik Falck

Abstract read
In one paragraph

Article in PeerJ, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Nawaf A NasserOttawa-Carleton Geoscience Centre and Department of Earth Sciences, Carleton University, Ottawa, ON, Canada.
R Timothy PattersonOttawa-Carleton Geoscience Centre and Department of Earth Sciences, Carleton University, Ottawa, ON, Canada.
Jennifer M GallowayGeological Survey of Canada (GSC)/Commission géologique du Canada, Natural Resources Canada (NRCan)/Ressources naturelles Canada (RNCan), Calgary, AB, Canada.ORCID 0000-0002-4548-6396
Hendrik FalckNorthwest Territories Geological Survey, Yellowknife, NT, Canada.ORCID 0000-0002-3767-8232

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Arcellinida (testate lobose amoebae) were examined from 40 near-surface sediment samples (top 0.5 cm) from two lakes impacted by arsenic (As) contamination associated with legacy gold mining in subarctic Canada. The objectives of the study are two folds: quantify the response of Arcellinida to intra-lake variability of As and other physicochemical controls, and evaluate whether the impact of As contamination derived from two former gold mines, Giant Mine (1938-2004) and Tundra Mine (1964-1968 and 1983-1986), on the Arcellinida distribution in both lakes is comparable or different. Cluster analysis and nonmetric multidimensional scaling (NMDS) were used to identify Arcellinida assemblages in both lakes, and redundancy analysis (RDA) was used to quantify the relationship between the assemblages, As, and other geochemical and sedimentological parameters. Cluster analysis and NMDS revealed four distinct arcellinidan assemblages in Frame Lake (assemblages 1-4) and two in Hambone Lake (assemblages 5 and 6): (1) Extreme As Contamination (EAC) Assemblage; (2) High calcium (HC) Assemblage; (3) Moderate As Contamination (MAC) assemblages; (4) High Nutrients (HN) Assemblage; (5) High Diversity (HD) Assemblage; and (6)

Indexed as

Bio-monitoringIntra-lake samplingLake sedimentsLegacy contaminationMultivariate analysisNorthwest Territories

Identifiers

PMID32411528
PMCPMC7204876

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.