Stand-level forest management for foraging and nesting of Williamson’s sapsuckers
Bibliographic record
Abstract
Williamson’s Sapsuckers, like most woodpeckers, require live and dead standing trees for foraging and nesting. Forest management plans that include Williamson’s Sapsucker habitat conservation guidelines currently focus on nesting trees because little is known about foraging habitat requirements, but foraging habitat in close proximity is also essential for the survival and reproduction of the species. We conducted a study on the selection of stand-level characteristics for foraging and nesting territories to improve knowledge on the habitat requirements of this endangered woodpecker in Canada during the breeding season. We tracked 27 radio-tagged Williamson’s Sapsuckers in managed forest at their northern range limit in two regions of southern British Columbia. We examined the selection of forest composition and configuration characteristics at the foraging patch and stand levels by comparing use and availability, and described foraging trip distances. In the Okanagan region, sapsuckers did not show a selection pattern for foraging patch characteristics. In the Western region, Williamson’s Sapsuckers selected foraging patches with higher densities of large live Douglas-fir trees. Nest patches were usually in small openings and had lower tree densities than foraging patches in the Western region, but not in the Okanagan region. Open areas (e.g., clear-cuts, seed tree cuts, pastures, roads, powerlines) were avoided during foraging trips in both regions. Regarding stand-level configuration, Williamson’s Sapsuckers selected continuous stands for foraging – with ≥30% crown closure in both regions. We used the 50th and 95th percentiles of foraging trip distances to recommend zones for nest reserve (no-harvest; 0–140 m from the nest) and nest management (Okanagan: 340 m, Western: 410 m). For the nest management zone, we recommend only partial harvesting with retained groups of trees extending from 140 to 340 m in the Okanagan region and from 140 to 410 m in the Western region. We suggest that Williamson’s Sapsuckers exhibited stronger selection when foraging in the Western region, because they compensated for longer foraging distances due to higher proportions of open area in their nesting territories.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".