Top–down influence of resident and overwintering Bald Eagles (<i>Haliaeetus leucocephalus</i>) in a model marine ecosystem
Bibliographic record
Abstract
Conservation of predators presents challenges when predators affect prey populations that provide ecosystem services. Near Puget Sound, resident and overwintering populations of Bald Eagle ( Haliaeetus leucocephalus (L., 1766)) have expanded in recent decades. We modeled the potential impact of Bald Eagles on marine food-web structure. Bald Eagles caused trophic cascade dynamics through mid-level predators (seabirds) to lower trophic levels (fishes, benthic invertebrates), particularly when seabirds were more abundant in eagle diets. Resident Bald Eagles affected food-web structure more than overwintering eagles, despite the latters’ greater abundance. Predator avoidance behavior by nearshore diving birds and herbivorous birds exacerbated trophic cascade effects, but only in a narrow range of species. Variability in the number of overwintering Bald Eagles, which come to the area to feed on salmon carcasses (primarily chum salmon, Oncorhynchus keta (Walbaum in Artedi, 1792)), had little effect on the food web. Our results indicate that Bald Eagles are important to marine food-web structure, owing to their high consumption rates and the high consumption rates of their seabird prey, but uncertainty about eagle diets limits our full understanding of their impact. In systems where Bald Eagles affect large seabird breeding colonies, their role in food-web structure is likely greater.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".