Hemlock looper outbreak: new insight about how Black-backed Woodpecker ( Picoides arcticus ) respond to resource pulses in eastern Canada
Bibliographic record
Abstract
Black-backed Woodpecker (Picoides arcticus) is known to benefit from pulse-resource disturbances in boreal forest for example, by colonizing recently burned habitats. Although insect outbreaks are ubiquitous in some parts of the eastern boreal forest, the opportunities offered by these natural disturbances for the Black-backed Woodpecker remain poorly understood. Between 2012 and 2014, a small-scale hemlock looper (Lambdina fiscellaria) outbreak occurred in central Québec (Canada) within the eastern boreal forest. Using global positioning system (GPS) tags, we documented home range sizes and habitat selections of Black-backed Woodpeckers at different scales and assessed nest survival 2–3 years post-outbreak. We tracked 5 birds and found 13 active nests. Mean home range size was 368 ± 134 ha. A negative relationship was observed between home range size and the proportion of area affected by hemlock looper-induced mortality. Mortality stands (> 75% tree mortality or severe defoliation, 70–100% foliage loss), were selected at both the landscape and home range scales, while light to moderate defoliated stands (1–69% foliage loss), were selected only at the landscape scale. At home range scale, nest site selection was predicted by the volume of early-decayed dead wood. The probability of nest sites being selected was greater than 50% when the average volume of early-decayed dead wood was greater than 61 m³/ha. At the tree scale, nest-tree selection was predicted by diameter at breast height (dbh) and tree type. The probability of nest-tree selection was greater than 50% when mean dbh was higher than 17.1 cm (mean nest dbh: 31.4 ± 1.7 cm) and woodpeckers preferred deciduous trees for nesting. We did not detect any temporal nor habitat variable effects on daily nest survival rate. The daily survival rate was 0.985 ± 0.007 and the nest success rate was 0.589 ± 0.147. Our results highlight that Black-backed Woodpeckers can benefit from pulse resources in stands affected by the hemlock looper 2–3 years after the outbreak. They are able to establish their home ranges, and successfully nest, despite logging operations that salvaged 38% of the affected stands.
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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 | 0.000 |
| Scholarly communication | 0.001 | 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".