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Record W3026862735 · doi:10.1111/eth.13036

Experimental tests of a seasonally changing visual preference for habitat in a long‐distance migratory shorebird

2020· article· en· W3026862735 on OpenAlexaff
Eva M. A. Kok, Jerry A. Hogan, Theunis Piersma

Bibliographic record

VenueEthology · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Toronto
FundersKoninklijk Nederlands Instituut voor Onderzoek der ZeeNederlandse Organisatie voor Wetenschappelijk Onderzoek
KeywordsHabitatCalidrisCaptivityTundraEcologyPreferencePlumageSeasonal breederMemorizationBiologyGeographyArcticPsychologyCognitive psychology

Abstract

fetched live from OpenAlex

Abstract Migratory shorebirds show highly organized seasonal cycles in physiological and morphological traits (body mass and composition, plumage, hormone levels, etc.), which in captivity is accompanied by restless behaviour at times when free‐living birds would start migration. We introduce the idea that seasonally changing preference for habitat could motivate migrants to embark on migration and that this cognitive process could also guide them to seasonally appropriate places. We explored this by testing whether red knots ( Calidris canutus ), which also in captivity maintain marked circannual phenotypic rhythms, show evidence of seasonal change in preference for pictures of seasonally appropriate habitats. We first developed a method to verify whether red knots are able to memorize and discriminate contrasting pictures projected by LCD projectors. This was followed by two different experiments in which we tested for a seasonally changing preference for breeding or non‐breeding habitat. When carried out during the pre‐breeding season, the red knots are expected to prefer pictures of mudflats, their non‐breeding habitat. At the start of the breeding season, they should prefer pictures of the tundra breeding habitat. We established that knots are able to distinguish and memorize projected images. We failed to demonstrate the predicted change in vision‐based habitat preference, but for reasons of test design we do not interpret this as a strong rejection of the hypothesis. Instead, we suggest that experiments with greater numbers of individuals tested once, perhaps in combination with the provision of additional cues such as smells and sounds, will help the development of these ideas further.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.737
Threshold uncertainty score0.128

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 head0.063
GPT teacher head0.306
Teacher spread0.243 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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