Response of terrestrial birds to climate-amplified shrub dominance in boreal mountains of Yukon, Canada
Bibliographic record
Abstract
Shrubs are expanding upslope and to higher latitudes due to increasing global temperatures, potentially affecting bird species that breed in subalpine, alpine, and tundra habitats. Studies have found variable non-linear relationships between bird abundance and shrub characteristics across latitudinal gradients in Alaska that indicate potential negative effects of shrubification (increases in woody plant growth, distribution, and relative abundance) on both alpine tundra and subalpine birds. Our study examined similar relationships between bird abundance and shrub dominance along elevational gradients at 10 montane sites in southwest Yukon, Canada. We assessed how vegetation (shrub height, density) and topography (elevation, aspect) influenced high elevation bird abundance, compared these relationships to those observed in Alaska, projected shrub expansion impacts at each of our 10 mountain sites, and identified bird species of potential conservation concern. Using autonomous recording units (ARUs) for bird surveys and conducting ground-based vegetation sampling, we modeled relationships between 17 bird species and vegetation and topography using GLMMs, and assessed potential shrub expansion using broad-scale landcover classification and historical examples of shrub expansion on mountains. Our results revealed: (1) the relative abundance of alpine-associated birds was affected primarily by vegetation, while subalpine-associated birds responded to both vegetation (shrub height, shrub stem count) and topography (elevation, aspect); (2) many species exhibited complex non-linear responses including positive and negative exponential relationships and threshold relationships, with several species showing peak relative abundance at moderate shrub heights or elevations; (3) projected shrub expansion would affect mountains inconsistently, potentially eliminating 90-100% of alpine bird habitat on four mountains under average expansion scenarios; and (4) both alpine- and subalpine-associated species may be at risk from climate amplified shrub expansion due to their negative or threshold responses to shrub dominance combined with restricted elevational ranges in the Yukon. These findings highlight the complexity and variability of mountain subalpine zones, the importance of broad-scale topography in driving bird species abundance, and the interplay between vegetation, topography, and bird distribution in sensitive northern mountain ecosystems.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".