Canopy microclimate and arboreal lichen loading in subalpine spruce-fir forest
Bibliographic record
Abstract
Hair lichen communities in Engelmann spruce (Picea engelmannii) subalpine fir (Abies lasiocarpa) forests of the northern Cariboo Mountains (British Columbia) show distinct vertical zonation. Alectoria sarmentosa reaches peak abundance in the lower canopy (over 35 kg/ha) whereas Bryoria spp. lichens reach peak abundance in the upper canopy (over 250 kg/ha). These distribution patterns are accentuated by stand structure with trees growing in clumps retaining significantly higher lichen loading on a per branch basis compared to solitary trees. The vertical zonation of lichen communities is accompanied by distinct trends in canopy microclimate. Snowmelt events account for the largest proportion of observed thallus hydration in both Alectoria and Bryoria. Although canopy microclimate is surprisingly isothermal during rainfall events, the attenuation of thallus hydration after wetting is typically greater for lower canopy exposures. An important exception to this pattern is seen under midwinter conditions, when solar insolation is insufficient to sustain prolonged lower canopy snowmelt. Our data support the hypothesis that ventilation in upper canopy exposures is a contributing factor in the vertical zonation of Alectoria and Bryoria communities. Upper canopy Bryoria rely more heavily on snowmelt events to sustain thallus hydration, whereas lower canopy Alectoria utilize summer rainfall events to a greater extent. We hypothesize that physiological mechanisms, through which these patterns of canopy microclimate influence lichen zonation, may include an intolerance to prolonged wetting by Bryoria and higher resaturation respiration costs in Alectoria, which would limit it to more mesic canopy exposures. We believe that the observed distribution of canopy lichens ultimately reflects the long-term interaction of both physiological and successional processes (lichen colonization and dispersal) within the canopy.Key words: canopy, epiphytes, lichens, microclimate.
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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".