Managing ecological traps: Logging and sapsucker nest predation by bears
Bibliographic record
Abstract
Abstract We tested the equal preference ecological trap hypothesis for breeding yellow‐bellied sapsuckers ( Sphyrapicus varius ) along a time‐since‐harvest gradient (1–5 yr, 16–20 yr, 21–25 yr, and >60 yr) in selection system‐logged hardwood forests in Algonquin Provincial Park, Ontario. Yellow‐bellied sapsuckers preferred 1–5 year and >60‐year‐old cuts equally and more than 16–20 year and 21–25‐year‐old cuts. More‐abundant arthropod food and/or higher‐quality sap resources may have attracted yellow‐bellied sapsuckers to 1–5 year and >60‐year‐old cuts. Only 52% of pairs raised fledglings in 1‐ to 5‐year‐old cuts during years when nest predation by American black bears ( Ursus americanus ) was common, the incidence of which was negatively related to increased availability of American beech ( Fagus grandifolia ) nuts from the previous autumn. By contrast, 88% of pairs raised fledglings in all years in >60‐year‐old cuts. One‐ to 5‐year‐old cuts were demographic sinks that represent equal‐preference ecological traps in years when nest predation by bears was common, whereas >60‐year‐old cuts were always demographic sources. High‐quality habitat cues for nesting yellow‐bellied sapsuckers appear to be retained for 1–5 years after selection system logging but fail to deliver safe nest sites. Cavities excavated in heart‐rot‐infected nest trees are least likely to be depredated because cavity walls are typically harder and deter entry by depredating bears. Retaining more potential nest trees per ha at harvest (especially American beech with heart‐rot) may increase the proportion of sapsucker nests that are excavated in bear‐resistant trees, thereby reducing nest predation and increasing fecundity. © 2012 The Wildlife Society.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".