and offspring sex ratios of red-winged blackbirds
Bibliographic record
Abstract
Abstract Predicting ecological consequences of climate change will be improved by understanding how species are affected by contemporary climate variation, partic-ularly if analyses involve more than single ecological variables and focus on large-scale climate phenomena. I used 18 years of data from red-winged blackbirds (Agelaius phoeniceus) studied over a 25-year period in eastern Ontario to explore chronological and climate-related patterns of reproduction. Although blackbirds started nesting earlier in years with warmer springs, associated with low winter values of the North Atlantic Oscillation Index (NAOI), there was no advance in laying dates over the study. Nesting ended progressively later and the breeding season lasted longer over the study, however, associated with higher spring values of NAOI. As the length of the nesting season increased, offspring sex ratios became more female biased, appar-ently as a result of females adjusting the sex of the eggs they laid, rather than from sex-biased nestling mortality. Clutch size did not vary systematically over the study or with climate. Opposing trends of declining nest success and increasing productivity of successful nests over the study resulted in no chronological change in produc-tivity per female. Higher productivity of successful nests was associated with higher winter NAOI values, possibly because synchrony between nesting and food availability was higher in years with high NAOI values. Other than the association between the start of nesting and spring temperatures, local weather (e.g., temperature, rainfall) patterns that linked NAOI with reproduction were not identified, suggesting that weather patterns may be complex. Because climate affected most aspects of red-winged blackbird reproduction examined, focusing on associations between climate and single variables (e.g., first-egg dates) will have limited value in predicting how future climates will affect populations.
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 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".