Differential habitat use by Acadian Nelson's sharp-tailed sparrows: implications for regional conservation
Bibliographic record
Abstract
ABSTRACT Nelson's Sharp-tailed Sparrows (Ammodramus nelsoni) that breed along the Atlantic coast of North America (Acadian subspecies subvirgatus) are considered saltmarsh specialists. However, these sparrows occasionally use upland habitats, such as hayfields. To evaluate the importance of hayfields as breeding habitat, we studied populations of A. n. subvirgatus in saltmarsh and hayfields in Nova Scotia, Canada, in 2004 and 2005. We monitored relative abundance and breeding phenology at 64 point-count stations (48 in hayfields and 16 in saltmarsh) and used an ordinal (0–5) observational index to quantify reproductive activity. A. n. subvirgatus showed more evidence of reproductive activity in saltmarsh (44% of point-count stations) than hayfields (28%; P= 0.07). However, there was no difference in either mean reproductive activity (saltmarsh = 0.83, hayfields = 0.53; P= 0.69) or mean relative abundance (saltmarsh = 0.27, hayfields = 0.26; P= 0.93). Although A. n. subvirgatus apparently breeds primarily in saltmarsh, hayfields appear to be an alternative breeding habitat. Use of hayfield habitat by A. n. subvirgtus, however, seems to vary between southern Maine and eastern Canada, suggesting that management plans will require approaches uniquely tailored to specific regions.
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".