Control of the annual cycle in birds: endocrine constraints and plasticity in response to ecological variability
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".