Association of the arboreal forage lichen<i>Bryoria fremontii</i>with<i>Abies magnifica</i>in the Sierra Nevada, California
Bibliographic record
Abstract
A strong positive association exists between Bryoria fremontii (Tuck.) Brodo & D. Hawksw. and red fir ( Abies magnifica A. Murray) in mixed-conifer forest of the south-central Sierra Nevada in California. The hypotheses that red fir microclimate, foliar leachate pH, mineral nutrients, and needle morphology may be especially favorable for B. fremontii were investigated in this study. There were no statistically significant differences in fall–winter–spring period within-crown vapor pressure deficits among five conifer species. In spring leachate solutions, NH4+and K+were significant indicators of red fir, which had generally greater ion concentrations than other species. Sugar pine ( Pinus lambertiana Douglas) leachate had the lowest pH. Mineral nutrient concentrations and acidity increased across species in fall samples. Growth and establishment of B. fremontii transplants were compared among the five conifer species. Grand mean annual transplant relative growth across conifer species was 6.28% with no statistically significant differences among species. Thallus retention in an establishment experiment was significantly greater in red fir than in shaded white fir ( Abies concolor (Gordon & Glend.) Hildebr. var. lowiana (Gordon) Lemmon) or the other three investigated conifers. The most important factor explaining the association of B. fremontii with red fir was the latter’s erect needle morphology.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".