Nonrandom territory occupancy by nesting Gyrfalcons (<i>Falco rusticolus</i>)
Bibliographic record
Abstract
We know little regarding how specific aspects of habitat influence spatial variation in site occupancy by Arctic wildlife, yet this information is fundamental to effective conservation. To address this information gap, we assessed occupancy of 84 Gyrfalcon (Falco rusticolus Linnaeus, 1758) breeding territories observed annually between 2004 and 2013 in western Alaska. In line with the theory of population regulation by site dependence, we asked whether Gyrfalcons exhibited a nonrandom pattern of site selection and if heterogeneous landscape attributes correlated with observed occupancy patterns. We characterized high- and low-occupancy breeding territories as those occupied more or less often than expected by chance, and we evaluated land cover at 1 and 15 km circles centered around nesting territories to identify habitat variables associated with observed occupancy patterns. We tested 15 competing models to rank hypotheses reflecting prey and habitat variables important to nesting Gyrfalcons. We confirmed a nonrandom pattern of site selection but found only weak evidence that the distribution of prey habitat was responsible for this pattern. We reason that preferential habitat use by nesting Gyrfalcons may be determined by spatial scales other than those we measured or may be driven by landscape-level attributes at time periods other than during the brood rearing period.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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; both teacher heads agree on what is shown here.
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".