A Meta‐Analysis of Bird Responses to Uniform Partial Harvesting across North America
Bibliographic record
Abstract
Most data on the effects of partial-harvest silviculture (where live trees are purposely retained at the time of harvest) on birds come from one or a few discrete harvesting treatments. It is thus difficult to infer species responses across a continuous gradient of tree retention from individual studies. To quantify the levels of tree retention expected to produce specified changes in the relative abundance of individual species, we carried out a meta-analysis of 42 studies that examined the impacts of uniform partial harvesting on North American birds. Of 34 species, sigmoidal models showed a negative effect of harvesting for 14 species and a positive effect for 6 species. Ovenbirds (Seiurus aurocapilla) and Brown Creepers (Certhia americana) were the species most sensitive to harvesting. Most of the 14 species that were negatively affected by harvesting showed 25%, 50%, and 75% reductions in abundance (relative to control sites) at tree retention levels ranging from 45 to 85%, 30-70%, and 15-50%, respectively. A few species, such as Yellow-rumped Warblers (Dendroica coronata), exhibited these levels of response at lower tree retention or were not predicted to decrease by 75% in harvested stands. Five of the 6 species that were positively affected by harvesting showed at least a 50% increase in abundance at nearly all levels of tree retention, although other early successional bird species did not appear to benefit from the relatively small openings created by uniform partial harvesting. Three of 20 species exhibited stronger responses to harvesting at a given level of tree retention in boreal and northern mixed forests of North America than other regions of the continent, but, with these exceptions, lack of variation among forest regions supported the broad-scale generality of species' responses to harvesting. The species response models we developed represent useful tools for evaluating stand-level impacts of partial harvesting on birds within an adaptive management framework. Uniform partial harvesting at light and, to a lesser degree, moderate intensities may be effective approaches to managing habitat for late successional bird species as part of broader ecosystem-based forest management.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.024 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".