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Record W2137073356 · doi:10.13034/cysj-2014-019

Rock snot and lake mud: exploring the history of recent blooms of Didymosphenia geminata using information contained in lake sediments

2014· article· en· W2137073356 on OpenAlexafffundvenueabout
J. Michelle Lavery, Joshua Kurek, Kathleen M. Rühland, Carole‐Anne Gillis, Michael F. J. Pisaric, John P. Smol

Bibliographic record

VenueJournal of Student Science and Technology · 2014
Typearticle
Languageen
FieldMaterials Science
TopicDiatoms and Algae Research
Canadian institutionsBrock UniversityInstitut National de la Recherche ScientifiqueQueen's University
FundersFondation Pour La Conservation Du Saumon Atlantique
KeywordsDiatomEcologyPaleolimnologyEnvironmental scienceOceanographyBenthic zonePlanktonBloomAquatic ecosystemEcosystemGeologyBiology

Abstract

fetched live from OpenAlex

Ecosystem managers have often considered the nuisance diatom species, Didymosphenia gemi¬nata (didymo) as being introduced to the natural environment through human activities; however, observations from early 20th-century surveys challenge this characterization. We use diatoms pre¬served in lake sediment cores to investigate the history of didymo blooms from Gaspésie, Quebec. Relative abundances of diatoms were examined from the dated sediments of Lac Humqui and Lac au Saumon (a lake with an inflowing river currently supporting blooms). Didymo was observed throughout the Lac au Saumon core, demonstrating that it has been present in the region well before the first reports of blooms in 2006. Lac Humqui diatom assemblages experienced a shift in composition with declines in benthic taxa (attached to substrates) and increases in planktonic (free floating) diatoms that began ~1970. Strong relationships between this diatom shift, and increases in regional air temperatures and earlier river ice-out dates were consistent with the expected effects of climate warming on aquatic systems. Our paleolimnological evidence shows that climate warming, rather than human introduction, likely plays an important role in triggering didymo blooms.

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)0.002
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.352
Threshold uncertainty score0.192

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.035
GPT teacher head0.293
Teacher spread0.259 · 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 designBench or experimental
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
Published2014
Admission routes4
Has abstractyes

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