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Record W6996498635

SELENIUM TRANSFER THROUGH THE PERIPHYTON-MACROINVERTEBRATE\nFOOD CHAIN AT A NORTHERN SASKATCHEWAN URANIUM MILL

2023· dissertation· en· W6996498635 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2023
Typedissertation
Languageen
FieldNursing
TopicSelenium in Biological Systems
Canadian institutionsnot available
Fundersnot available
KeywordsTrophic levelFood chainBioaccumulationBenthic zoneMacrophyteInvertebratePrimary producersAquatic ecosystemBioindicatorPeriphyton
DOInot available

Abstract

fetched live from OpenAlex

Anthropogenic activities, particularly coal-fired plants and coal and metal mining can increase aqueous selenium (Se) concentrations in aquatic ecosystems. The historical and present aquatic Se contamination in North America has been linked to adverse reproductive and developmental effects on fish and aquatic birds. Consequently, the environmental monitoring of Se in the receiving water bodies often focuses on potential adverse effects on aquatic vertebrates. But the magnitude to which Se bioaccumulates in the environment, potentially causing toxic effects in higher trophic levels, is dictated by Se dynamics at the base of aquatic food chains. Yet, limited understanding of the processes involved in Se uptake by primary producers, microorganisms and particulate matter and trophic transfer to different invertebrate taxa remains, generating great uncertainty in the modelling of Se in higher trophic levels. The potential influences of season on Se bioaccumulation, particularly by overwintering aquatic biota, represents an additional challenge to Se modelling and risk assessment in boreal ecosystems. \nThe goal of this research was to investigate Se distribution, uptake, and bioaccumulation in the periphyton-benthic macroinvertebrates food chain of a boreal lake (McClean Lake) receiving continuous low-level (< 1 µg/L) Se input from a uranium mill in northern Saskatchewan, and to refine site-specific Se risk assessment at this site. In the summers 2018 and 2019, ten sampling stations representing different degrees of uranium mill effluent exposure were selected to assess aqueous Se bioaccumulation potential in periphyton and benthic macroinvertebrates (BMI): two stations were placed at a high effluent exposure site upstream from Mclean Lake (Vulture Lake inlet and outlet), seven stations were placed on McClean Lake east basin (EB), including one near the effluent diffuser site, and another one towards Collins Creek outlet. The tenth station was a reference site located in McClean Lake west basin (WB) for comparison to background results. In winter 2021, sampling efforts were reduced, and Se bioaccumulation potential was investigated only at McClean Lake EB (sites 4, 5, 8 and 9). In summer 2019 and winter 2021, periphyton and BMI were sampled using sediment grab samples. Selenium concentrations measured at the base of the food web were subsequently incorporated into biodynamic models to estimate Se body burdens in resident fish species (northern pike, white sucker, lake whitefish and nine spine stickleback). \nHigher Se concentrations in surface water (2.3 ± 0.3 µg/L), sediment (9.4 ± 1.4 µg/g d.w.), periphyton (13.0 ± 2.4 µg/g d.w.) and BMI (10.3 ± 4.2 µg/g d.w.) were observed at high-effluent exposure sites in Vulture Lake. However, Se concentrations in periphyton (16.7 ± 4.4 µg/g d.w) and some benthic detritivore taxa (6.0 ± 0.4 µg/g d.w) sampled near the effluent diffuser site on McClean Lake (Sites 4 and 9) reached levels comparable to those sampled at the high effluent exposure site (TSe > 2µg/L). Moreover, significant differences in Se bioaccumulation among benthic primary consumer taxa within sites were observed; the bivalve genus Sphaerium was considered a poor Se accumulator (1.25 ± 0.1 µg/g d.w), whereas the caddisfly genus Agrypnia was a potential Se hyper-accumulator (12.0 ± 4.7 µg/g d.w). Furthermore, the shorter deployment duration used for the artificial substrates in 2018 (5 vs. 7 weeks) seemed to have influenced Se bioaccumulation levels in BMI. Based on effluent distribution in McClean Lake traced using electrical conductivity (EC) measured with autonomous sensors (Libelium) and Se bioaccumulation in periphyton and benthic primary consumers sampled in 2018 and 2019 using artificial substrates (Hester-Dendys), a theoretical Se threshold for protection of fish populations of 0.7 ± 0.2 µg/L was derived for McClean Lake. \nAdditional field and laboratory studies were conducted in 2019 and 2021 to clarify Se results from periphyton and BMI sampled with the artificial substrates and the derived total aqueous Se thresholds for protection of resident fish of McClean Lake. Selenium bioconcentration in biofilms was substrate-dependent, with significantly higher Se concentrations in biofilms growing on artificial substrates (2.4 ± 1.5 µg/g d.w) relative to those collected from top-layer sediment (1.1 ± 1.3 µg/g d.w). Moreover, significantly higher Se bioconcentrations were observed in winter (3.5 ± 1.0 µg/g d.w) relative to summer (1.1 ± 1.3 µg/g d.w). Differences in Se concentrations in periphyton and BMI influenced by sampling method and season translated into differences in estimated fish body burdens and derived tissue-based aqueous Se benchmarks for McClean Lake EB. Overall, estimated and observed Se body burdens were below national and site-specific benchmarks for total Se in fish tissue and overall risks of adverse effects of Se on fish populations were considered low. Significantly lower tissue-based aqueous Se benchmarks were calculated for McClean Lake EB in summer (artificial substrates: 0.7 µg/L, grab samples: 2.5 µg/L) relative to winter (12 µg/L), suggesting a higher Se bioaccumulation potential at the former. This is the first study to date to document the direct effects of sampling strategies, low water temperature, and prolonged ice-cover period on Se bioaccumulation at the base of an aquatic food web. Collectively, the findings presented herein provide practical considerations for future Se study designs and will help inform decision-making processes related to Se risk assessment and management in boreal ecosystems receiving continuous, low-level Se input.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0030.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.185
Teacher spread0.174 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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