HABITAT USE AND PRODUCTIVITY OF SHARP-SHINNED HAWKS NESTING IN AN URBAN AREA
Bibliographic record
Abstract
We measured productivity and vegetation parameters of habitat quality at 16 Sharp-shinned Hawk (Accipiter striatus) nests in and near the greater Montreal area in order to evaluate nesting habitat use and its possible relationship to reproductive success in an urban setting. Mean clutch size was 4.4 and hatching success was 3.8 eggs per nest. At least one egg hatched in 11 of 16 nests (68.8%), 10 (62.5%) pairs raised young to a bandable age (≥10 days old), and 8 (50%) pairs successfully produced at least one fledgling. Immature individuals comprised 33.3% of male and 38.5% of female breeders. Mean values in the habitat assessment included nest tree height, 14.0 m; tree density, 955/ha; total canopy cover, 88.1%; coniferous cover, 39.7%; mean dbh, 17.6 cm; and distance to the nearest forest opening, 19.7 m. Sharp-shinned Hawks nested in a range of forest types, from mature conifer plantations to young, almost purely deciduous stands, and this population exhibited considerable flexibility with respect to most of the habitat features that we measured. Their use of older stands with more deciduous cover than those used by conspecifics elsewhere may reflect regional differences in habitat availability as well as in the abundance of competitor species. Breeding in an urbanized area does not seem to be detrimental to Sharp-shinned Hawks, as evidenced by this population’s relatively large proportion of immature breeders and normal productivity, which appeared to be independent of all the assessed parameters of habitat quality.
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 | 0.000 |
| 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) | 0.001 | 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".