Factors affecting the availability of thick epiphyte mats and other potential nest platforms for Marbled Murrelets in British Columbia
Bibliographic record
Abstract
Nest platforms (mossy pads, limbs, and deformities >15 cm in diameter) are key requirements in the forest nesting habitat of the threatened Marbled Murrelet ( Brachyramphus marmoratus (J.F. Gmelin, 1789)). Little is known about factors that affect the availability of platforms or the growth of canopy epiphytes that provide platforms. We examined variables affecting these parameters in coastal trees in British Columbia using data from 29 763 trees at 1412 sites in 170 watersheds. Tree diameter (diameter at breast height (DBH)) was the most important predictor of platform availability in the pooled data and within each of six regions. In most regions, platforms become available at DBH > 60 cm, but on East Vancouver Island, DBH needs to be >96 cm and possibly on the Central Coast >82 cm. Other regional predictors of platforms included tree height, tree species, and to a lesser extent elevation, slope, and latitude. Most (72%) trees providing platforms had epiphytes (mainly moss) covering one third or more of branch surfaces and 81% had intermediate or thick epiphyte mats. Mistletoe deformities provided <7% of platforms. Our model predictions help to define and manage suitable habitat for nesting Marbled Murrelets and also contribute to understanding forest canopy 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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".