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Assessing the Recovery of Lakes in Southeastern Canada from the Effects of Acidic Deposition

2003· article· en· W4251484564 on OpenAlexaboutno aff
D. S. Jeffries, Thomas A. Clair, Suzanne Couture, Peter J. Dillon, Jacques Dupont, Wendel Keller, Donald K. McNicol, Michael A. Turner, Robert Vet, Russell Weeber

Bibliographic record

VenueAMBIO · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAlkalinityEnvironmental scienceAcid depositionAquatic ecosystemNova scotiaAcid rainNitrateEcosystemSulfateFish killDeposition (geology)Environmental protectionEcologyOceanographyChemistrySedimentGeologyBiologyAlgal bloomNutrient

Abstract

fetched live from OpenAlex

Reductions in North American sulfur dioxide (SO2) emissions promoted expectations that aquatic ecosystems in southeastern Canada would soon recover from acidification. Only lakes located near smelters that have dramatically reduced emissions approach this expectation. Lakes in the Atlantic provinces, Quebec and Ontario affected only by long-range sources show a general decline in sulfate (SO42−) concentrations, but with a relatively smaller compensating increase in pH or alkalinity. Several factors may contribute to the constrained (or most likely delayed) acidity response: declining base cation concentrations, drought-induced mobilization of SO42−, damaged internal alkalinity generation mechanisms, and perhaps increasing nitrate or organic anion levels. Monitoring to detect biological recovery in southeastern Canada is extremely limited, but where it occurs, there is little evidence of recovery outside of the Sudbury/Killarney area. Both the occurrence of Atlantic salmon in Nova Scotia rivers and the breeding success of Common Loons in Ontario lakes are in fact declining although factors beyond acidification also play a role. Chemical and biological models predict that much greater SO2 emission reductions than those presently required by legislation will be needed to promote widespread chemical and latterly, biological recovery. It may be unrealistic to expect that pre-industrial chemical and biological conditions can ever be reestablished in many lakes of southeastern Canada.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.674
Threshold uncertainty score0.817

Codex and Gemma teacher scores by category

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

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 head0.005
GPT teacher head0.194
Teacher spread0.189 · 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.

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

Citations29
Published2003
Admission routes1
Has abstractyes

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Same venueAMBIOSame topicFish Ecology and Management StudiesFrench-language works237,207