The Effect of Kleptoparasitic Bald Eagles and Gyrfalcons on the Kill Rate of Peregrine Falcons Hunting Dunlins Wintering in British Columbia
Bibliographic record
Abstract
Kleptoparasitism in birds has been the subject of much research, and the Bald Eagle (Haliaeetus leucocephalus) is a known kleptoparasite. It has been reported to pirate ducks captured by Peregrine Falcons (Falco peregrinus), but ours is the first study to examine the effect of kleptoparasitic Bald Eagles on the kill rate of shorebird-hunting Peregrines and indirectly on a population of Dunlins (Calidris alpina) wintering in coastal British Columbia. Bald Eagles increased seasonally and yearly from October 2008 to January 2011. When eagles were scarce, Peregrines hunted ducks as well as Dunlins. Conversely, when eagles were numerous Peregrines hunted Dunlins only. In 56 instances, one or more eagles closely followed hunting Peregrines and retrieved 13 Dunlins dropped or downed by the falcons. The Peregrines were also kleptoparasitized by Gyrfalcons (Falco rusticolus), which pirated 11 Dunlins from Peregrines. Observed losses to kleptoparasites amounted to 24 (36%) of 67 Peregrines' captures. The kill rate per hour of observation was 0.05 hr-1 in October and November when eagles and Gyrfalcons were few but significantly higher at 0.18 hr-1 during January and February. In January 2011, when intraguild kleptoparasites were most abundant, the Peregrine's kill rate was 0.30 hr-1. These results support the hypothesis that kleptoparasites had an indirect effect on a population of wintering Dunlins because Peregrines compensated for prey lost to kleptoparasites by increasing their kill rate.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".