DOES PREY BIOMASS OR MERCURY EXPOSURE AFFECT LOON CHICK SURVIVAL IN WISCONSIN?
Bibliographic record
Abstract
Past studies suggest that the productivity of common loons (Gavia immer) is lower on acidic lakes in northern Wisconsin, USA, than on neutral lakes. Two hypotheses have been proposed to explain low chick survival: (1) reduced food consumption related to changes in prey communities on lower pH lakes and (2) high mercury (Hg) exposure on lower pH lakes. To address these hypotheses, we quantified prey and Hg consumption by loon chicks on 51 lakes and survival on 55 lakes ranging in pH from 4.9 to 9.5 in northern Wisconsin in 1995 and 1996. The time adults spent providing prey to chicks was unrelated to lake pH but increased with number of chicks and chick age. The number of prey caught per provisioning time declined as lake pH declined because adults made fewer dives, not because success of prey capture declined. Chicks consumed more insect larvae on acidic lakes and more crayfish (Family Astacidae) on neutral lakes. Biomass consumed ranged from an average 1.99± 1.05 (SE) g/hr/chick during the first week of a chick's life to a peak of 7.93 ± 1.93 g/hr/chick during the eighth week. Biomass intake per chick body weight (g/Wg/hr) declined with lake acidity but was not related to chick survival (P = 0.25). Although the Hg concentration in the 3 major prey species was positively related to lake acidity and blood Hg level of chicks at a lake, total Hg consumption (µg/Wg/hr) was highest on moderately acidic lakes rather than on the most acidic lakes. We suggest that loon chick survival in northern Wisconsin lakes is more likely related to prey availability than to Hg exposure. When we removed from our analysis 1 lake where 211-day-old chicks were killed by predators, chick survival was negatively related to lake acidity but not to biomass or Hg consumption. We discuss mechanisms of Hg excretion that may allow young chicks to survive on acidic lakes in northern Wisconsin despite high Hg intake.
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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".