Habitat use by Pileated Woodpeckers at two spatial scales in eastern Canada
Bibliographic record
Abstract
To study the multiple spatial scale pattern of habitat use by Pileated Woodpeckers (Dryocopus pileatus L.), we compared the vegetation characteristics at used sites with those at unused sites at macrohabitat (154 ha radius plots) and microhabitat (ca. 0.04 ha radius plots) scales in the La Mauricie region of Québec. Used macrohabitats were those in which woodpeckers were detected at playback stations. Used microhabitats corresponded to sites showing signs of foraging (i.e., excavated cavities). Pileated Woodpeckers responded to vegetation structure at both scales sampled. Macrohabitats used by woodpeckers had relatively low percentages of mixed shade-intolerant hardwood stands, coniferous stands, and stands of relatively low stem density and tree height, but included high percentages of 51- to 90-year-old stands. Microhabitats used by woodpeckers were characterized most strongly by a high density of large snags but also by a high density of small-diameter snags and a low density of shade-intolerant hardwood trees and coniferous trees [Formula: see text]30 cm diameter at breast height. The concordance between the observed and predicted use of micro- and macro-habitat plots was independent of spatial scale (logistic regression, χ20.05,1 = 1.8, P = 0.18, n = 429), suggesting that habitats use by woodpeckers was influenced to a similar extent by habitat features measured at both spatial scales. Because Pileated Woodpeckers are likely to require specific habitat features at different spatial scales, forest-management guidelines intended to conserve this umbrella species should consider a multiple spatial scales approach.
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 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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".