Forest birds and forest management in Ontario: Status, management, and policy
Bibliographic record
Abstract
This paper presents a summary of presentations and discussions at a 3-day workshop on research and management of forest birds in Ontario forests. While many forest birds in Ontario do not appear to be negatively affected over the long term by forest management, some species were noted as declining using Breeding Bird Atlas data and more research is required to understand the causes, some of which may well be related to habitat change on the wintering grounds. For example, the aerial foragers as a group have declined significantly during the past 20 years. Recent research suggests landscape convergence between managed and fire-origin stands for bird species over time, but negative effects were suggested for boreal chickadee (Poecile hudsonsicus), brown creeper (Certhia familiaris), and some cavity-users, although there is no evidence of declines in these species from the current atlas data. This inconsistency needs to be evaluated. In Carolinian forests, even small-scale tree harvesting in this already highly fragmented landscape can have deleterious effects on breeding success for some species, such as wood thrush (Hylocichla mustelina) and rose-breasted grosbeak (Pheucticus ludovicianus). New modelling techniques and meta-analyses seem to hold considerable promise as tools to help managers understand key habitats, species that require special attention, and as predictive models of forest management effects. A large number of recommendations to improve the management of forest birds are provided and as is a suggested research agenda to improve our understanding of key factors affecting birds in managed forests. Key words: forest birds, forest management, boreal forest, Great Lakes–St. Lawrence forest, Carolinian forest, indicators, modelling, cavity nester, spruce budworm, forest policy, Ontario
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".