Long-term decline in a red-winged blackbird population: ecological causes and sexual selection consequences
Bibliographic record
Abstract
Habitat loss and large-scale climate phenomena are widely implicated as causing decline in animal populations. I examined how both factors contributed to a precipitous decline in an Ontario red-winged blackbird (Agelaius phoeniceus) population using 16 years of data collected between 1974 and 1995. The decline was manifested as an almost 50% reduction in mean harem size, which reduced the opportunity for sexual selection threefold. Regional hay production, which should affect recruitment into the study population, also declined substantially. Correlation between blackbirds and hay may be coincidental, however, because annual changes in harem size were not associated with annual changes in hay production. This study coincided with an unprecedented positive phase of the North Atlantic Oscillation (NAO). Changes in harem size were correlated with winter NAO index values, suggesting that winter mortality contributed to the population decline. Positive correlation between harem size change and male return rates also supported the winter mortality hypothesis. Continued declines will cause this blackbird population to change from socially polygynous to socially monogamous. Study of red-winged blackbird winter ecology is needed to identify the proximate causes of mortality, whereas breeding studies can explore the consequences of relaxed sexual selection.
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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 | 0.000 |
| 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) | 0.001 | 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".