Habitat selection of the sagebrush Brewer’s sparrow Spizella breweri breweri in British Columbia
Bibliographic record
Abstract
When animals cluster their territories within larger patches of seemingly appropriate habitat it could mean that they have additional, finer scale habitat requirements or that non-habitat cues play a role in their selection decisions. Sagebrush Brewer’s Sparrows (Spizella breweri breweri) cluster their territories throughout their breeding range. I examined territory-scale selection by the species using two approaches: observation of individual selection for vegetation characteristics, and an experimental test of conspecific attraction. Within a suitable range of shrub cover (where clustering occurs), vegetation characteristics did not predict individual selection decisions or breeding success. However, more males established territories in response to playbacks than untreated controls, indicating that conspecific attraction may play a role in Brewer’s Sparrow habitat selection. These results suggest that traditional habitat models, which consider only resource distributions and not social factors, may be inadequate for the conservation of this and similar species.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".