The influence of habitat diversity and structure on bird use of riparian buffer strips in coastal forests of British Columbia, Canada
Bibliographic record
Abstract
I investigated the role of habitat structure in explaining bird species richness and abundance in riparian buffer strips of old-growth coniferous forest on western Vancouver Island, British Columbia. Using buffer strips of varying widths and a control from undisturbed riparian forest, I tested the hypothesis that vegetation differs in buffer strips of varying width. I selected 10 summary variables to represent broad-scale vegetation attributes of riparian habitat. Deciduous tree density was higher, and shrub richness was lower in wide buffers compared with narrow buffers. I then used Akaike information criterion to examine whether vegetation structure or buffer width best explained patterns of bird richness and abundance in riparian habitats. Species richness and abundance in several foraging guilds were explained better by buffer width than by vegetation. Abundances of three bird habitat guilds: riparian specialists, forest-interior, and open-edge species, and 6 of 10 species were best explained by specific vegetation features. Differences in vegetation, particularly deciduous tree density and shrub cover, explained part of the variation in abundance of several riparian forest-dwelling species and may be useful in evaluating specific forest management practices. Because deciduous tree density is also positively correlated with buffer width, wide buffers (>100 m) may benefit not only those species associated with coniferous upland forests and forest generalists sensitive to buffer width, but also those species whose abundance is associated with deciduous trees.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".