Food Quantity Affects the Sensitivity of <i>Daphnia</i> to Road Salt
Bibliographic record
Abstract
Road deicing operations have raised chloride (Cl) levels in many temperate lakes in Europe and North America. These lakes vary widely in trophic status, but to date, no one has quantified the interaction between food quantity and road salt toxicity. We examined the effects of food quantity (particulate algal C concentration (C)) on the chronic toxicity of Cl to Daphnia in soft-water bioassays. There was a strong positive linear relationship (r(2) = 0.92 for NaCl and r(2) = 0.96 for CaCl2) between food quantity and Cl LC50. As food quantity increased from 0.2 to 1.0 mg C/L (levels characteristic of oligotrophic to eutrophic lakes, respectively), the chronic Cl LC50 increased from 55.7 to 284.8 mg Cl/L. Salt type (NaCl or CaCl2) did not affect the Cl LC50, Daphnia life history parameters, or the intrinsic rate of population increase (r). The life history parameter most sensitive to Cl was neonate production. Cl did not inhibit egg production, nor was the maternal lipid investment in eggs changed, but egg viability and the subsequent release of live neonates decreased as Cl levels increased and food decreased. Our results suggest the trophic status of lakes should be considered when assessing ecological threat from Cl.
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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 | 0.001 |
| 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".