Will environmental calcium declines hinder<i>Bythotrephes</i>establishment success in Canadian Shield lakes?
Bibliographic record
Abstract
Recently, calcium-rich daphniids have declined on the Canadian Shield in response to falling lake-water calcium concentrations, or [Ca]. Meanwhile the invader Bythotrephes longimanus , a predator that feeds on Daphnia , continues to spread. Our goal was to determine if ongoing calcium declines might directly or indirectly affect Bythotrephes ’ establishment success. To address direct effects, we provide the first quantification of Bythotrephes’ calcium content, which is very low (0.03% as dry mass) compared with other Cladocera. We also examined the effects of differing [Ca] (0.1–2.6 mg·L–1) on Bythotrephes’ performance in the laboratory. For all [Ca], population growth rates remained positive, indicating that Bythotrephes has great tolerance of low [Ca]. Finally, we examined Bythotrephes’ distribution in relation to [Ca] on the Shield where is it relatively new, alongside its distribution in Norway where it is endemic and found that Bythotrephes inhabits very low calcium environments in Norway (minimum = 0.2 mg·L–1). These results suggest that Bythotrephes establishment in Canada is currently not — and in the future will likely not — be limited by falling calcium. Rather, as Bythotrephes is more tolerant of low [Ca] than are its daphniid prey, we propose that both calcium decline and Bythotrephes invasions may contribute to Daphnia decline.
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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 | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".