Postlogging Succession and Habitat Usage of Shrubland Birds
Bibliographic record
Abstract
ABSTRACT In the first decades after logging, the vegetation structure of harvested areas changes rapidly due to succession. For shrubland birds, many of which specialize on regeneration of specific ages, the changing vegetation structure makes determining how much habitat is available for individual species difficult. We conducted a meta‐analysis to determine how populations of shrubland birds in the eastern United States and Canada respond to succession in the first 20 years after timber harvest. Based on those results, we used the area under the abundance‐time regression curves to estimate the proportion of regenerating forest actually used by each bird species. Of the 28 species for which we had sufficient data, 14 showed significant changes in abundance over time. For 6 species, abundance was highest immediately after logging and decreased thereafter. Abundances of 7 other species were initially low, peaked roughly 10 years after harvest, and declined thereafter. Based on these results, shrubland birds would be expected to occupy a mean of just 53% (SD = 17%) of regenerating forests up to 20 years old. Thus, current estimates of habitat availability for shrubland birds may be too high by a factor of 2. Our findings also suggest that managed openings should be maintained on longer rotations than are currently used, providing habitat for birds that prefer older regeneration.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".