Why is brood reduction in Florida scrub-jays higher in suburban than in wildland habitats?
Bibliographic record
Abstract
In a population of Florida scrub-jays, Aphelocoma coerulescens (Bosc, 1795), in a suburban scrub habitat, partial brood loss is much more common (averaging about 30% of nestlings from successful nests) than in a natural habitat (averaging about 5%). We hypothesized that this partial brood loss was attributable to starvation of last-hatched nestlings (i.e., brood reduction), and that large differences in partial brood loss were caused by differences in arthropod food abundance between the two sites. To test these hypotheses, we closely monitored nests in suburban scrub in 1999 and performed arthropod surveys and focal-nest observations in both habitats in 1998 and 1999. In suburban scrub, later hatched nestlings were three times more likely to die before fledging than earlier hatched nestlings, suggesting that brood reduction occurred. In both years, arthropod abundance in the suburban scrub was less than half that of the natural scrub. However, patterns of food delivery by parents were not significantly different between sites, suggesting that lower food abundance does not in itself explain higher partial brood loss in suburban habitat. Differences in the number of helpers, a greater degree of hatching asynchrony or the delivery of lower quality food throughout the nestling period may increase the probability that later hatched nestlings starve in suburban scrub.
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".