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Record W3108813865 · doi:10.1111/jav.02623

Causes and consequences of variation in diet composition of nestling Canada jays

2020· article· en· W3108813865 on OpenAlexaffabout
Nikole E. Freeman, Amy E. M. Newman, Alex O. Sutton, Kurt Kyser, D. Ryan Norris

Bibliographic record

VenueJournal of Avian Biology · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsNature Conservancy of CanadaQueen's UniversityUniversity of Guelph
Fundersnot available
KeywordsBiologyPasserineEcologyHatchingPopulationPredationSeasonal breederReproductionBorealInvertebrateZoologyDemography

Abstract

fetched live from OpenAlex

Diet quality during development can impact growth, physiology, behaviour and survival. The Canada jay is a resident boreal passerine that caches a wide variety of perishable food items in late summer and autumn for its over‐winter survival and late‐winter reproduction. A previous experiment found evidence that food supplementation of Canada jay pairs during the nestling period had a positive effect on the condition of their nestlings. However, given that foods cached by adults vary widely in nutritional content, the composition of nestling diets could also have an important influence on offspring development. In a population of Canada jays in Algonquin Provincial Park, Ontario, Canada, we investigated the influence of environmental conditions before and during the breeding season on nestling diet composition and the consequences of nestling diet composition on the body condition of nestlings and on their subsequent survival. Using stable‐carbon (δ 13 C) and ‐nitrogen (δ 15 N) isotopes, we estimated the proportion of three food groups (vertebrates + human food, invertebrates and plants) in feathers from almost 200 nestlings. Nestling diet in March and April was influenced by environmental conditions 5–6 months prior to hatching, with warmer and more variable autumn temperatures associated with a greater proportion of vertebrate flesh and human food in the diet. However, the proportion of vertebrates and human food in the diet had no influence on nestling body condition or whether an individual was observed the following fall. Our results, in conjunction with previous work on Canada jays, suggest that the quantity of food available to a nestling during development may be more important than diet composition.

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 score0.210
Threshold uncertainty score0.994

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 studies0.0000.000
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 head0.018
GPT teacher head0.237
Teacher spread0.220 · 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

Citations6
Published2020
Admission routes2
Has abstractyes

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