Nickel toxicity in wood frog tadpoles: Bioaccumulation and sublethal effects on body condition, food consumption, activity, and chemosensory function
Bibliographic record
Abstract
Abstract Nickel (Ni) concentrations in aquatic ecosystems can be amplified by anthropogenic activities including resource extraction. Compared with fish and invertebrates, knowledge of Ni toxicity in amphibians is limited, especially for northern species. We examined the effect of Ni on wood frog (Lithobates sylvaticus) tadpoles, the species with the widest and most northern distribution of any anuran in North America. Wood frog tadpoles were exposed to a Ni concentration gradient (0.02–5.5 mg/L of Ni at 164 mg/L as CaCO3 water hardness) for 8 d and examined for lethality, Ni bioaccumulation, and several sublethal endpoints including body condition, food consumption, activity, and chemosensory function. Nickel induced a sublethal effect on body condition (8-d 10 and 20% effect concentrations [EC10 and EC20] of 1.07 ± 0.38 and 2.44 ± 0.51 mg/L of Ni ± standard error [SE], respectively) but not on food consumption, activity, or chemosensory function. Nickel accumulation in tadpole tissues was positively related to an increase in aqueous Ni concentration but was not lethal. Both the acute and chronic US Environmental Protection Agency water quality guideline concentrations for Ni (0.71 and 0.08 mg/L at 164 mg/L as CaCO3 water hardness, respectively) were protective against lethal and sublethal effects in wood frog tadpoles. In the present study, wood frog tadpoles were protected by current water quality guidelines for Ni and are likely not as useful as other taxa for environmental effects monitoring for this particular metal. Environ Toxicol Chem 2018;37:2458–2466. © 2018 SETAC Abstract The body condition of wood frog tadpoles decreases with an increase in the accumulation of nickel (Ni) in the whole body.
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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 | 0.000 | 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 | 0.001 |
| 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".