The growth rate of Black-tailed Gull chicks is negatively related to total mercury of female parents on Kabushima (Kabu Island), Japan
Bibliographic record
Abstract
The mercury (Hg) contamination at high concentrations affects the physiological state and behavior of animals, however, the effects of low Hg exposure on avian breeding success and the impact on the growth of chicks that depend on feeding from their parents are unclear. We investigated the effects of maternal Hg concentrations on breeding success in a colony of Black-tailed Gulls (Larus crassirostris) breeding on Kabushima, northeastern Honshu, Japan, in 2018 and 2019. Total Hg concentrations in blood cells in females were 2.48 ug/g dry weight ± 0.55 (1.28–3.28) in 2018 and 2.42 ug/g dry weight ± 0.55 (1.87–3.29) in 2019. In our two-year field study, female parents did not differ in Hg concentrations between two years, but δ15Ns, i.e., the difference in diet, were significantly lower in 2019 than those in 2018. The difference in δ15Ns could be related to difference in fledging success between two years (90% and 40% in 2018 and 2019, respectively). However, the results of this study showed that Hg exposure was not significantly associated with clutch size, hatching success, or nest success in the two years with different diets and was not significantly associated with any reproductive parameters at δ15N. Hg exposure was significantly negatively correlated with chick weight gain (g/day), while blood Hg accumulation in female Black-tailed Gulls was below the threshold for direct effects on breeding success. However, there was no noticeable abnormal behavior when feeding the chicks at their Hg exposure levels, under the current level value. Although the breeding numbers of Black-tailed Gulls are not thought to be declining at colonies around Japan at the moment, Hg contamination may threaten their numbers in the future.
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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 | 0.000 |
| 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".