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Record W2562461123 · doi:10.1139/er-2016-0054

The ecological impacts of lakewater calcium decline on softwater boreal ecosystems

2016· article· en· W2562461123 on OpenAlexafffundvenue
Adam Jeziorski, John P. Smol

Bibliographic record

VenueEnvironmental Reviews · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsEcologyAquatic ecosystemEnvironmental scienceWatershedEcosystemBorealFreshwater ecosystemBiology

Abstract

fetched live from OpenAlex

In recent decades, marked declines in calcium (Ca) concentrations have been noted in many softwater boreal lakes, and are believed to be a long-term consequence of acid deposition as well as other stressors (such as timber harvesting). Reduced Ca availability may act as a potent environmental stressor. Investigations of the direct ecological impacts of lower Ca concentrations in freshwater systems have largely focused on Ca-rich members of the Cladocera; however, a growing body of work, spanning several scientific fields, suggests Ca decline will have profound direct and indirect consequences for aquatic ecosystems. Here, we synthesize recent laboratory analyses and field surveys to provide an overview of these consequences, while highlighting paleolimnological investigations that provide some long-term perspective on the phenomenon. However, considerable questions remain regarding ‘baseline’ or pre-impact conditions, due to the accelerated leaching of Ca from watershed soils during the period of anthropogenic influence. Furthermore, catchment-specific differences in both leaching rates and the initial size of the Ca pool in watershed soils complicate determination of the eventual endpoints of the declines. Despite these uncertainties, persistent low Ca concentrations are anticipated to impede biological recovery from lake acidification, and that ongoing declines will have cascading effects throughout aquatic ecosystems due to the loss of vulnerable taxa. To better understand how reduced Ca availability will continue to change affected surface waters and how these changes will interact with other environmental stressors will require continued investigation of the declines from multiple scientific perspectives.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.187
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0030.005

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 head0.028
GPT teacher head0.260
Teacher spread0.232 · 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; both teacher heads agree on what is shown here.

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

Citations55
Published2016
Admission routes3
Has abstractyes

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