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Record W7099029856

Studies in Avian Biology No. 14:71-83, 1990. Allocation of Time and Energy FLEXIBLE TIME BUDGETS IN BREEDING COMMON MURRES: BUFFERS AGAINST VARIABLE PREY ABUNDANCE

2015· article· en· W7099029856 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFossil Insects in Amber
Canadian institutionsnot available
Fundersnot available
KeywordsCapelinPredationTime budgetAbundance (ecology)Forage fishFish <Actinopterygii>Herring
DOInot available

Abstract

fetched live from OpenAlex

Abstract. We report on a 4-year study of the relationships between parental behavior of Common Murres (Uris aalge) and the relative abundance of their principal prey, capelin (Mallotus villosus), at Witless Bay, Newfoundland. Capelin comprised 89 % of the prey fed to rnurre chicks. Capelin abun-dance and the density of their schools, measured with hydroacoustic surveys, varied significantly within and between each of the murre’s breeding seasons, by up to IO-fold. Despite this, the feeding rates of chicks (average 0.28 fish chick- ’ h-l) did not vary significantly between years, and were not depressed by intraseasonal capelin variations. Adult murres compensated for periods of low capelin abundance by taking more of other fish, particularly sandlance (Ammodytes sp.), and by spending more time at sea. Chick survival (average 93%) did not vary significantly between years. Chick feeding rates and parental resting time at the colony were not strongly affected by weather, sea conditions or chick age. We suggest hat with moderate prey abundance, variable time budgets of adult murres would buffer the effects of temporal and spatial prey variability so that chick feeding rates would remain relatively constant. Under such conditions chick growth and survival might not reflect food availability. Key Words: Seabird; fish abundance; time budgets; energetics; murre; capelin.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.725
Threshold uncertainty score0.654

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.045
GPT teacher head0.274
Teacher spread0.229 · 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 designBench or experimental
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

Citations0
Published2015
Admission routes1
Has abstractyes

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