Avian Reporting Rates in Chugcheongnam Province, South Korea Depend on Distance from Forest Edge, Size of Trees, and Size of Forest Fragments
Bibliographic record
Abstract
Forests provide bird communities with various resources, including food and habitats. Thus, forest attributes, such as size, structure, and species composition, influence the distribution and dynamics of bird species. This study was conducted to examine the association between forest condition, bird species abundance, and diversity within Chungcheongnam Province, South Korea. Zero-inflated binomial regression models were used to analyze a total of 1646 sampling points of abundance and diversity. Forest area, distance to forest edge, and tree size class were selected as covariates. Negative associations between forest area and overall bird abundance and species richness were indicated, whereas distance to forest edge was not a significant factor. This insignificance may be attributed to the relatively small, fragmented, and homogenous forest areas across the studied region. Results for individual bird species indicated that six out of the 35 major bird species had significant associations to the forest edge and three species showed a preference for the interior of the forest. The results of this study imply that other factors, such as food availability and biotic interaction, are more important when determining habitat preference in a relatively homogenous area with a long history of human disturbance.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".