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Record W1974455837 · doi:10.1098/rstb.2007.0004

Control of the annual cycle in birds: endocrine constraints and plasticity in response to ecological variability

2007· review· en· W1974455837 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePhilosophical Transactions of the Royal Society B Biological Sciences · 2007
Typereview
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsDawson College
FundersNatural Environment Research Council
KeywordsBiologyphotoperiodismEcologyMoultingFlexibility (engineering)Duration (music)Phenotypic plasticityEntrainment (biomusicology)BreedPeriod (music)Day lengthRhythmLarva

Abstract

fetched live from OpenAlex

This paper reviews information from ecological and physiological studies to assess how extrinsic factors can modulate intrinsic physiological processes. The annual cycle of birds is made up of a sequence of life-history stages: breeding, moult and migration. Each stage has evolved to occur at the optimum time and to last for the whole duration of time available. Some species have predictable breeding seasons, others are more flexible and some breed opportunistically in response to unpredictable food availability. Photoperiod is the principal environmental cue used to time each stage, allowing birds to adapt their physiology in advance of predictable environmental changes. Physiological (neuroendocrine and endocrine) plasticity allows non-photoperiodic cues to modulate timing to enable individuals to cope with, and benefit from, short-term environmental variability. Although the timing and duration of the period of full gonadal maturation is principally controlled by photoperiod, non-photoperiodic cues, such as temperature, rainfall or food availability, could potentially modulate the exact time of breeding either by fine-tuning the time of egg-laying within the period of full gonadal maturity or, more fundamentally, by modulating gonadal maturation and/or regression. The timing of gonadal regression affects the time of the start of moult, which in turn may affect the duration of the moult. There are many areas of uncertainty. Future integrated studies are required to assess the scope for flexibility in life-history strategies as this will have a critical bearing on whether birds can adapt sufficiently rapidly to anthropogenic environmental changes, in particular climate change.

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.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.308
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.008
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.045
GPT teacher head0.313
Teacher spread0.268 · 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