Factors Influencing the Distribution of Northern Spotted Owls in the Eastern Cascades, Washington
Bibliographic record
Abstract
The Northern Spotted Owl (Strix occidentalis caurina) population is declining throughout its range in the United States and adjacent Canada and is facing increasing pressure from the invading Barred Owl (Strix varia). In this study, we characterize Spotted Owl habitat associations and develop 2 new habitat selection models for the eastern Washington Cascade Range. Topographic and habitat data were compiled at 2 scales (0.25 and 1.0 mi) around 224 Spotted Owl activity centers, or sites, and at 160 random locations in the same geographic region, and used to develop models for predicting owl distributions. Univariate analysis found that owl sites occurred below 5000-ft elevation and were more likely to occur as area in the >71% crown-cover class increased. Owl sites were found to be more likely to occur closer to streams and to be rare in the Subalpine Fir (Abies lasiocarpa) vegetation type. The 9–25″ tree size-class was a significant predictor of the distribution of owl sites. Habitat models were constructed that were moderately successful at predicting owl-site distribution. Models from the largest scale tested (1.0-mi radius) were the most predictive, at 80% accuracy. Top-ranked models included overstory canopy cover, tree size, elevation, precipitation, distance to stream, and tree species as predictors. The resulting models can be used to help identify likely sites for surveys and to inform conservation and landscape management activities associated with forest-health restoration.
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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 | 0.001 |
| 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".