Woodpeckers and other excavators maintain the diversity of cavity‐nesting vertebrates
Bibliographic record
Abstract
Woodpeckers and other excavators create most of the holes used by secondary cavity nesters (SCNs) in North American temperate mixedwood forests, but the degree to which excavators release SCNs from nest-site limitation is debated. Our goal was to quantify how excavators maintain the diversity and abundance of secondary cavity nesters in a temperate forest through the creation of tree cavities. We examined the short- and long-term (legacy) effects of excavators (principally woodpeckers, but also red-breasted nuthatches and black-capped chickadees) on forest biodiversity using longitudinal monitoring data (1,732 nest cavities, 25 sites, 16 years) in British Columbia, Canada. Sites with higher densities of excavator nests had more cavities available, higher species richness of SCNs and higher nest density of SCNs, indicating the importance of a standing stock of cavities. Years with higher nesting densities of excavators were followed by years with higher SCN diversity, indicating that the creation of nesting opportunities through fresh excavation releases SCNs from community-wide nest-site limitation. We also show that excavators leave a 'legacy' of biodiversity (species richness and abundance) at a site by accumulating cavities at rates faster than they become unusable by decay or destruction. By quantifying site-level effects of cavity excavation on the SCN community, our study highlights the key role of excavators as ecosystem engineers that maintain forest wildlife biodiversity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".