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Record W3090436948 · doi:10.5194/hess-24-4763-2020

Ionic aluminium concentrations exceed thresholds for aquatic health in Nova Scotian rivers, even during conditions of high dissolved organic carbon and low flow

2020· article· en· W3090436948 on OpenAlexafffundabout
Shannon Sterling, Sarah MacLeod, Lobke Rotteveel, Kristin Hart, Thomas A. Clair, Edmund A. Halfyard, Nicole O’Brien

Bibliographic record

VenueHydrology and earth system sciences · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMine drainage and remediation techniques
Canadian institutionsDalhousie University
FundersFisheries and Oceans CanadaFondation Pour La Conservation Du Saumon AtlantiqueAtlantic Canada Opportunities Agency
KeywordsDissolved organic carbonDeposition (geology)Nova scotiaAluminiumEnvironmental chemistryEnvironmental scienceTotal organic carbonAquatic ecosystemSTREAMSAcid depositionHydrology (agriculture)ChemistryOceanographySoil waterGeologySoil scienceSediment

Abstract

fetched live from OpenAlex

Acid deposition released large amounts of aluminium into streams and lakes during the last century in northern Europe and eastern North America. Elevated aluminium concentrations caused major environmental concern due to aluminium's toxicity to terrestrial and aquatic organisms and led to the extirpation of wild Atlantic salmon populations. Air pollution reduction legislation that began in the 1990s in North America and Europe successfully reduced acid deposition, and the aluminium problem was widely considered solved. However, accumulating evidence indicates that freshwater systems still show delays in recovery from acidification, with poorly understood implications for aluminium concentrations. Here, we investigate spatial and temporal patterns of labile cationic forms of aluminium (Al i ) from 2015 to 2018 in 10 catchments in Nova Scotia, Canada; this region was one of the hardest hit by acid deposition, although it was not considered to have an aluminium problem due to its high dissolved organic carbon (DOC) concentrations that were expected to reduce Al i concentrations. Surprisingly, our results show the widespread and frequent occurrences of Al i concentrations that exceed toxic thresholds in all sampled rivers despite high DOC concentrations. Generalized linear mixed model results reveal that DOC, instead of being inversely related to Al i , is the strongest predictor (positive) of Al i concentrations, suggesting that the recruitment properties of DOC in soils outweigh its protective properties in streams. Lastly, we find that, contrary to the common conceptualization that high Al i levels are associated with storm flow, high Al i concentrations are found during base flow. Our results demonstrate that elevated Al i concentrations in Nova Scotia continue to pose a threat to aquatic organisms, such as the biologically, economically, and culturally significant Atlantic salmon ( Salmo salar ).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.163
Threshold uncertainty score0.329

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.234
Teacher spread0.222 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations22
Published2020
Admission routes3
Has abstractyes

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