Influence of tree species on epiphytic macrolichens in temperate mixed forests of northern Italy
Bibliographic record
Abstract
Tree species is a key factor in shaping epiphytic lichen communities. In managed forests, tree species composition is mainly controlled by forest management, with important consequences on lichen diversity. The main aim of this work was to evaluate the differences at tree level in macrolichen richness and composition between Abies alba Mill. and Fagus sylvatica L. in a temperate mixed forest in northern Italy, in addition to evaluating two different proportions of the two species at the stand level. Abies alba and F. sylvatica host lichen communities including several rare and sensitive species. Our findings indicate that both tree species were important for lichen diversity, since they hosted different communities. However, F. sylvatica proved to be a more favourable hosting tree for several rare and sensitive species. Species associated with A. alba were mainly acidophytic lichens, while those associated with F. sylvatica were foliose hygrophytic lichens, mainly establishing over bryophytes. The frequency of the flagship species Lobaria pulmonaria (L.) Hoffm. was a valuable predictor of cyanolichen richness and was useful in identifying sites hosting lichen communities that are potentially more sensitive to thinning and human disturbance. The results support the relevance of mixed A. alba – F. sylvatica formations among European habitats worthy of conservation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".