Growth of epiphytic old forest lichens across climatic and successional gradients
Bibliographic record
Abstract
This paper aims to assess the influence of canopy cover on lichen growth in boreal forests along a regional forest gradient. Biomass and area gain, and some acclimation traits, were assessed in the old-forest lichens Lobaria pulmonaria (L.) Hoffm., Pseudocyphellaria crocata (L.) Vain., and Usnea longissima Ach. transplanted 110 days in three successional Norway spruce ( Picea abies (L.) Karst.) forest stands (clearcut, young, and old forest) repeated along a rainfall gradient (continental, suboceanic, and Atlantic zones) in Scandinavia. Lichen growth peaked in Atlantic rainforests with mean dry matter (DM) gain up to 36%–38%. The alectorioid lichen U. longissima showed the widest range of growth responses and no signs of chlorophyll degradation. Its highest DM gain consistently occurred in clearcuts, whereas the DM gain was close to zero in the shadiest young forest. The two foliose lichens L. pulmonaria and P. crocata exhibited maximal growth rates in old forests, but apparently growth was limited by low light even in old forests. Their DM gain was reduced in the most sun-exposed clearcuts due to chlorophyll degradation and was relatively high under closed young canopies, suggesting a better adaptation to shade. The lichen responses show that a high frequency and dominance of young and dense fast-growing forest stands at a landscape level are not compatible with large populations of these old-forest lichens and that a lack of lichens under an industrial forestry regime may not necessarily be determined by low dispersal efficiency only.
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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 | 0.000 | 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) | 0.000 | 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".