Evidence of negative seasonal carry‐over effects of breeding ground mercury exposure on survival of migratory songbirds
Bibliographic record
Abstract
Mercury (Hg) is a well‐known global contaminant that persists in the environment. The organic form, methylmercury (MeHg) has been shown to adversely affect bird immune function, foraging behavior, navigation, and flight ability, which individually or together could reduce migration performance, and ultimately survival. Nestlings grow feathers at their natal site, and in North America many adult passerines undergo a complete feather molt prior to autumn migration at or near their breeding location. Body Hg is redistributed into growing feathers, and remains stable following feather growth. As flight feathers are retained in most species over the non‐breeding season until molt in the following summer, tail feathers can be used at other times and places as indicators of Hg body burden on the breeding grounds. In five migratory passerine species, we compared Hg concentrations in tail feathers that were grown prior to autumn migration and retained until the following spring. We predicted that we would observe a shift in the distribution of species‐specific feather Hg values towards lower means in the spring if Hg reduced survival over the migration and winter periods. We found reductions in mean feather Hg between autumn and spring in two long‐distance migratory insectivores (blackpoll warbler Setophaga striata ; American redstart Setophaga ruticilla ). Most significantly, spring‐returning blackpoll warblers, a species that undertakes long non‐stop flights to South America during autumn migration, had nearly 50 percent lower Hg concentrations than those that departed in the autumn. Our finding suggests that Hg exposure on the breeding areas could have a carry‐over effect to influence migration success and survival of insectivorous songbirds that undergo extensive and demanding migratory journeys. More investigation is needed to fully understand the relationships among Hg exposure, migration performance, and survival of songbirds.
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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 | 0.000 |
| 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".