Factors associated with nest- and roost-burrow selection by burrowing owls (<i>Athene cunicularia</i>) on the Canadian prairies
Bibliographic record
Abstract
We examined nest- and roost-burrow characteristics from a declining population of burrowing owls (Athene cunicularia (Molina, 1782)) in Saskatchewan. Between 1992 and 2003, 84% of the 584 nests we found were in grassland pastures, even though these pastures constituted only 7% of the potentially available nesting area within our study area. In contrast, less than 3% of nests were in crop fields, despite these fields comprising 90% of the potentially available area. Within grassland pastures, owls selected nest burrows in areas with a higher density of burrows within 75 m (11.1 burrows/ha) compared with non-nest burrows of similar dimensions (5.6 burrows/ha). Richardson's ground squirrels (Spermophilus richardsonii (Sabine, 1822)) and badgers (Taxidea taxus (Schreber, 1777)) are the primary excavators of suitable nesting burrows in prairie Canada. In our study area, burrowing owls chose to nest and roost in badger-sized burrows, selecting those with taller tunnel entrances and soil mounds relative to unused burrows. We suggest that management for burrowing owl nesting habitat in Canada should consider the owls' avoidance of crop fields and their preference for grassland pastures. Managers should also consider the owls' apparent preference for nesting in areas of high burrow densities and their selection of badger-sized burrows for nesting and roosting.
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 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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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 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".