Contrasting the abundance, nitrogen, and carbon of epiphytic macrolichen species between host trees and soil types in a sub-boreal forest
Bibliographic record
Abstract
Differences in lichen diversity and abundance and lichen N and C pools were examined across the two dominant host tree species ( Picea engelmannii Parry ex Engelm. × Picea glauca (Moench) Voss) and Abies lasiocarpa (Hook.) Nutt.)) and two soil types (fine- and coarse-textured soils) in an old-growth sub-boreal forest in central British Columbia, Canada. Forty-four epiphytic macrolichen species were identified across the study area. Hair lichen species, particularly nonsorediate Bryoria species, were more abundant in spruce on coarse-textured soils, while cyanolichens were most commonly observed in subalpine fir on fine-textured soils. Overall macrolichen biomass and C pools were greatest in subalpine fir trees on coarse-textured soils. The tripartite species Lobaria pulmonaria (L.) Hoffm. was the dominant macrolichen, particularly over fine-textured soils where its stand level biomass was greater than that of all other species combined. The N pools of L. pulmonaria in combination with the less abundant N-rich bipartite cyanolichens amounted to 7.5 ± 1.9 kg N·ha–1on fine-textured soils. These results indicate that epiphytic cyanolichens may make substantial contributions to ecosystem N despite their relatively insignificant contributions to overall forest biomass and C stocks.
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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 | 0.001 |
| 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".