Give a Hoot: evaluating population augmentation efforts of the Western Burrowing Owl (Athene cunicularia hypugeae) in Canada
Bibliographic record
Abstract
Migratory animals are a growing conservation concern and present unique challenges to \npopulation augmentation programs. Quantitatively evaluating and monitoring augmentation \nefforts is critical for conservation success. My research formally evaluated the success of two \nWestern Burrowing Owl (Athene cunicularia hypugaea) population augmentation programs in \nManitoba and British Columbia using survival, recruitment, and reproduction. Manitoba’s headstarting program holds hatching year (HY) owls overwinter taken from the nests of previous \ncaptive-released pairs. After being overwintered in human care, the HY owls are released in pairs \nas second year (SY) owls. British Columbia has a breeding and release program where owls are \nbred in facilities; their offspring are then held overwinter, paired and soft-released in the spring. \nBoth programs soft-release SY pairs that lay clutches in the wild and young are referred to as \n“wild-hatched owls”. In British Columbia, wild-hatched owls returned significantly more than \ncaptive-released (ß = 1.05±0.29, p < 0.001). Holding animals overwinter may hinder accurate \nmigratory behaviour. Fewer owls returned to release sites with more cropland (p = 0.049). \nReleases should be prioritized at sites with low percentages of cropland. Interestingly, \nindividuals who returned from migration to form pairs and breed had significantly higher \nreproductive success than captive-released pairs (p < 0.001), suggesting effects of survivor-bias \nor mate choice. My thesis has identified opportunities to implement research with a priori \nhypotheses and data-driven management directions for the conservation of Burrowing Owls in \nCanada.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".