El Niño drives timing of breeding but not population growth in the song sparrow ( <i>Melospiza melodia</i> )
Bibliographic record
Abstract
Increasing evidence suggests that climate change affects the timing of breeding in birds, but there is less evidence to show how such changes affect the population dynamics of birds overall. Over the past 43 years, song sparrows (Melospiza melodia) on Mandarte Island, British Columbia, Canada have not shown an advance in breeding date in response to global warming. However, this population did show considerable annual variation in timing of breeding correlated with the El Niño Southern Oscillation. Birds bred earlier in warmer El Niño years and later in colder La Niña years. Early breeding strongly increased reproductive output. However, annual variation in timing of breeding had little effect on population growth, perhaps because the population is strongly regulated by the rate of recruitment by juveniles. The juvenile recruitment rate declined with increasing population density but showed little response to climate. These findings suggest that populations will vary in response to climate change depending on how climate affects the demographic parameters that contribute most to population growth.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".