Decreases in diatom cell size during the 20th century in the Laurentian Great Lakes: a response to warming waters?
Bibliographic record
Abstract
Several authors have postulated that lake warming favors diatom taxa characterized by smaller cell sizes and suggested that this phenomenon may affect freshwater phytoplankton communities worldwide. Here, we examined historical (~1900–2015) trends in diatom cell size in the Laurentian Great Lakes. Cell size decreased in Lakes Superior, Erie and Ontario, while no significant trends were observed for Michigan and Huron. In Lakes Superior and Ontario, cell size within species decreased over the course of the 20th century, suggesting demographic shifts toward smaller, later-generation individuals. Contrastingly, species-specific mean cell size increased in Michigan and Erie, likely as a result of accelerated loss rates during summer stratification. Size-specific rates of relative abundance change (larger taxa decreased while smaller taxa increased), were observed in all lakes except Michigan. These shifts toward communities dominated by smaller celled taxa either reinforced (Superior, Huron, Ontario) or dampened (Michigan, Erie) the influence of demographic shifts. Notwithstanding the influences of multiple stressors on diatom cell size at the within-lake scale, we demonstrated a gradual (5.11 µm3/y) decline in mean diatom cell size across the basin. Historical, basin-wide decreases in cell size demonstrate the likelihood of climate change driving changes in the primary producer community of large, freshwater systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".