Habitat selection and fidelity by White-throated Sparrows (<i>Zonotrichia albicollis</i>): generalist species, specialist individuals?
Bibliographic record
Abstract
Individuals from habitat generalist species are often thought to be habitat generalist themselves, but this assumption should be examined in light of mounting evidence for native and phenotypic habitat preference. We experimentally tested whether the White-throated Sparrow ( Zonotrichia albicollis (Gmelin, 1789)) exhibits habitat preferences at the individual level. The White-throated Sparrow was a habitat generalist species in our study area, with high occupancy of clearcuts as well as mature forests. However, males in mature forests whose territories were clear-cut in the winter following their breeding season (n = 14), dispersed twice as far as males from uncut mature forests (n = 21). New territories selected by males after clearcuts contained significantly more mature forest than what remained in the territory that they abandoned, but not as much mature forest as was found in their former territory. Gain in uncut habitat after dispersal was positively correlated with dispersal distance. Clear-cut locations left vacant by dispersing males were colonized by new conspecifics. Our results suggest that individual sparrows use only a subset of their species’ wide range of habitats. We question the assumption that individuals from a generalist species are versatile and unlikely to be affected by habitat disturbance.
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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) | 0.001 | 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".