Rock snot and lake mud: exploring the history of recent blooms of Didymosphenia geminata using information contained in lake sediments
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".