Limited evidence for the influence of the physical structure and floristics of habitat on a boreal forest bird community
Bibliographic record
Abstract
Studies conducted at regional and continental scales show that avian richness, community composition, and abundance are associated with variation in the vegetation physical structure and community composition (floristics) within broad habitat types. The relative contributions of physical structure and floristics are contested, and relationships are often taxon-specific. We used 110 microphone arrays deployed across 90 sampling locations and two breeding seasons to survey an avian community in the boreal forest in Labrador, Canada. Our objectives were (1) to describe the avian community of an underrepresented portion of the boreal forest, (2) to estimate the relationships between avian species richness and habitat characteristics, (3) to estimate if species detection at a given location was related to local habitat characteristics, and (4) to investigate the spatial and temporal patterns of the avian community composition. We detected 32 species at our sampling locations; physical structure and floristics were not related to avian species richness, although estimates of richness were higher on warmer days and lower on windier days. Habitat characteristics were associated with the detection of Boreal Chickadee (Poecile hudsonicus), Yellow-rumped Warbler (Setophaga coronata), American Robin (Turdus migratorius), and Black-throated Green Warbler (Setophaga virens). Finally, avian community composition was only moderately consistent among three categorical forest types and between audio sampling periods in two consecutive breeding seasons. Overall, we show that the structural and floristic traits measured at our study site are not related to the detection of most avian species or to species richness.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".