Does postharvest silviculture improve convergence of avian communities in managed and old-growth boreal forests?
Bibliographic record
Abstract
Habitat change following forest management may reduce biodiversity in boreal forests, as it has done globally in many forest types. Postharvest silviculture (PHS) is implemented to improve the yield of commercial tree species and has been applied to large areas of boreal forests. PHS may also influence animal communities and so we assessed songbird responses to these treatments in stands 20–52 years old in Ontario, Canada. We expected that several old-forest species would respond positively to PHS, that avian assemblages in treated forests would be distinct from those in untreated managed forests regardless of age, and that assemblages in our oldest treated stands would begin to converge with those of mature unmanaged forests. PHS stands had higher conifer density than naturally regenerating managed stands. The avian assemblage differed between treated and untreated stands at 20–30 years but not at 31–52 years. Convergence with old-forest assemblages was incomplete at 31–52 years after harvesting, although abundances of seven of 13 old-forest species did not differ from those in unmanaged forests. Of 10 old-forest species with competitive models, only Bay-breasted Warbler (Setophaga castanea (Wilson, 1810)) responded positively to PHS at the stand level, whereas two species responded positively at the landscape scale. Brown Creeper (Certhia americana Bonaparte, 1838), Boreal Chickadee (Poecile hudsonicus Forster, 1772), and Blackburnian Warbler (Setophaga fusca (Müller, 1776)) were absent from most managed stands and so require specific attention in planning for forest management, including retention of old-forest and delaying harvest of second-growth stands to ensure their occurrence and persistence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".