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Record W1940159843 · doi:10.22621/cfn.v129i2.1696

Kleptoparasitism by Bald Eagles (<em>Haliaeetus leucocephalus</em>) as a factor in reducing Peregrine Falcon (<em>Falco peregrinus</em>) predation on Dunlin (<em>Calidris alpina</em>) wintering in British Columbia

2015· article· en· W1940159843 on OpenAlexafffundvenueabout
Dick Dekker, Mark C. Drever

Bibliographic record

VenueThe Canadian Field-Naturalist · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsEnvironment and Climate Change Canada
FundersSimon Fraser University
KeywordsPeregrinusFalconBald eaglePredationKleptoparasitismGeographyPopulationBayFisheryCalidrisAccipitridaeLarusEcologyBiologyFish <Actinopterygii>ArchaeologyDemography

Abstract

fetched live from OpenAlex

Kleptoparasitism, or food piracy, is common in a wide range of taxa, particularly among predators, with the larger species forcing smaller species to surrender their catch. The Bald Eagle (Haliaeetus leucocephalus) is known to rob Peregrine Falcons (Falco peregrinus) of just-caught prey. We present time series of kleptoparasitic interactions between eagles and peregrines hunting Dunlin (Calidris alpina) that were wintering at Boundary Bay in the Fraser River valley, British Columbia. In 1108 hours of observation during January, intermittently between 1994 and 2014, we recorded 667 sightings of Peregrine Falcons, including 817 attacks on Dunlin resulting in 120 captures. The population of wintering Bald Eagles in the study area increased from about 200 in 1994 to 1800 in 2014, while the rate of kleptoparasitism at the expense of peregrines increased from 0.05 to 0.20. The increase in the number of Bald Eagles coincided with a decline in January sightings of Peregrine Falcons, which suggests that some falcons may have left the study area because of interference from eagles. The decrease in Peregrine Falcon numbers can be expected to have led to reduced predation risk for Dunlins. Christmas Bird Counts conducted in the Fraser River Valley have underscored the fluctuation in eagle and peregrine numbers reported here.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.844

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.017
GPT teacher head0.241
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2015
Admission routes4
Has abstractyes

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