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Intraspecific Variation in Commuting Distance of Marbled Murrelets (Brachyramphus marmoratus): Ecological and Energetic Consequences of Nesting Further Inland

2001· article· en· W2178869500 on OpenAlexaffabout
Cindy L. Hull, Gary W. Kaiser, Cecilia Lougheed, Lynn W. Lougheed, Sean Boyd, Fred Cooke

Bibliographic record

VenueThe Auk · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsSimon Fraser UniversityNatural Sciences and Engineering Research Council of Canada
Fundersnot available
KeywordsForagingNest (protein structural motif)Seasonal breederEcologyRange (aeronautics)Marbled meatIntraspecific competitionBiologyForageFisheryGeographyAnimal science

Abstract

fetched live from OpenAlex

Radio transmitters were deployed on Marbled Murrelets (Brachyramphus marmoratus) at Desolation Sound, British Columbia, Canada, during the 1998 breeding season to assess individual variation in distance birds nested from foraging areas, and potential energetic and ecological consequences of commuting those distances. Radio-tracking from a helicopter was used to locate nests, and tracking from the air and boats was used to locate murrelets on the water. Twenty-three nests were found, with active incubation at 16, and active chick-rearing at 12. A minimum of 3 nests fledged chicks, 9 were failures, and 11 were unknown. Nests were at an elevation of 806 ± 377 m and a distance of 39.2 ± 23.2 km (range 12–102 km) from locations on the water. Birds spent an estimated 1.2 ± 0.7 h per day commuting to and from nests (range 0.3–3.5 h per day). It was estimated that birds expended 3,883 ± 2,296 kJ (range 1,200–10,144 kJ) over the breeding season when commuting to those nests, which was 5–41% of their estimated field metabolic-rate during the breeding season. There was no relationship between distance to nests and breeding success. Either Marbled Murrelets can accommodate that additional energy expenditure, or reduce commuting costs by modifying their foraging behavior. They may forage closer to nest sites when provisioning chicks, thereby reducing commuting costs with a payload, or alter nest visitation rates in relation to distance they nest from foraging areas. Nests further inland may also confer advantages that compensate for the added commuting, or birds might replenish body reserves at the end of the breeding season.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.019
Threshold uncertainty score0.456

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.226
Teacher spread0.212 · 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 teacher head, 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

Citations44
Published2001
Admission routes2
Has abstractyes

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