Foraging ecology of Endangered Williamson’s Sapsuckers in Canada : multi-scale habitat selection in two biogeoclimatic zones
Bibliographic record
Abstract
Williamson’s Sapsuckers are Endangered woodpeckers in Canada that breed in montane forests only in British Columbia and require protection of their critical habitat. While there is reasonable knowledge of their distribution and nesting habitat requirements, there are knowledge gaps regarding foraging habitat of Williamson’s Sapsuckers. I investigated the selection of foraging habitat in managed forest at the foraging substrate and patch scales using visual observations of foraging behaviour of 27 radio-tagged Williamson’s Sapsuckers in the two biogeoclimatic zones where they are found in Canada, the Montane Spruce and Interior Douglas-fir. The characteristics of foraging trees differed with foraging mode and nesting status, but not with bird gender or age. Williamson’s Sapsuckers preferred large live Douglas-fir (> 22.5 cm dbh) for gleaning and sap feeding in both biogeoclimatic zones, while trees used for pecking were mostly large dying western larch in the Montane Spruce zone and large dead ponderosa pine in the Interior Douglas-fir zone. At the foraging patch scale, Williamson’s Sapsuckers did not prefer any stand-level characteristics in the Montane Spruce zone, while in the Interior Douglas-fir zone, they selected foraging patches with higher densities of their preferred foraging substrate (i.e., large live Douglas-fir). Areas of open habitat and single trees were avoided during foraging trips in both biogeoclimatic zones and this habitat type was found in significantly lower proportions in the Montane Spruce than in the Interior Douglas-fir zone. Williamson’s Sapsuckers showed no significant preferences for within-stand configuration characteristics (retained groups, forest edges, open stands and closed stands) in the Montane Spruce zone, but they preferred foraging along forest edges and in closed stands in the Interior Douglas-fir zone. I used foraging trip distances to recommend nest reserve (no-logging; 0-140 m from the nest) and nest management zones. For the nest management zone, I recommend only partial harvesting with retained groups of trees extending from 140-340 m in the Montane Spruce zone and from 140-410 m in the Interior Douglas-fir zone. My study on Williamson’s Sapsuckers is the first to provide a comprehensive representation of foraging habitat requirements for the species.
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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 | 0.001 | 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) | 0.001 | 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".