Data from: Mercury concentrations decline with age in the fur of females of an insectivorous terrestrial mammal (Myotis lucifugus)
Bibliographic record
Abstract
Methylmercury (MeHg) is a toxic form of mercury that bioaccumulates in organisms and biomagnifies through food webs. MeHg concentrations can be high in aquatic environments, and this puts high trophic-level predators who derive energy originating from aquatic environments at risk of toxic effects. Due to the potential for bioaccumulation of MeHg over an individual’s life, the risk of MeHg toxicity may increase as animals age, and this risk may be especially high in species with relatively high metabolic rates. Total mercury (THg) concentrations were measured from the fur of adult female little brown bats (Myotis lucifugus) collected between 2012–2017 in Salmonier Nature Park, Newfoundland and Labrador. Using linear mixed-effects models, the effects of age, year, and day of capture on THg concentrations were evaluated and interpreted with AICc and multi-model inference. We expected that THg concentrations would increase with age, and that due to annual summer moulting, individuals captured earlier in the season would have lower THg concentrations than individuals captured later in the season. Contrary to expectations, THg concentrations decreased with age, and date of capture did not explain any variation in concentration. Among individuals, there was a negative relationship between the initial THg concentration of an individual and the rate of change in THg concentrations with age. Using a regression analysis, we found evidence of a population-level decline in THg concentrations in fur over the 6-year study period. Overall, the results indicate that adult female bats eliminate enough MeHg from their tissues to affect a decrease in THg concentrations in their fur over time and that young adults are potentially at the greatest risk of experiencing toxic effects from high MeHg concentrations; this could result in reduced reproductive output, and warrants further research.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".