Dynamics of epiphytic macrolichen abundance, diversity and composition in boreal forest
Bibliographic record
Abstract
Summary Epiphytic macrolichen lichens are important components of forest ecosystems, but their responses to stand‐replacing fire and multiple successional pathways of the canopy tree layer are poorly understood. We examined the dynamics of epiphytic macrolichens following wildfire and tested the independent and interactive effects of time since fire and overstorey composition on epiphytic macrolichen abundance, diversity and composition in boreal forests of Canada. Epiphytic macrolichens were sampled in 51 stands of conifer, mixed‐wood and broadleaf overstorey types ranging from 7 to 209 years since fire. Macrolichen abundance estimated as percentage cover continuously increased with stand age with highest cover in 209‐year‐old stands for all overstorey types. Mixed‐wood and conifer stands had higher macrolichen abundance than broadleaf stands in all age classes except similarly low abundances in stands ≤15 years old for all overstorey types. Species richness of epiphytic macrolichens reached peaks in 98‐ or 146‐year‐old stands. Mixed‐wood stands had higher macrolichen species richness than broadleaf and conifer stands at 98 years old, but not at other age classes. Multivariate analysis indicated that the macrolichen communities were compositionally distinct for all age classes and overstorey types. Synthesis and applications . Epiphytic macrolichen abundance continuously increases with time since fire. Our results also show that macrolichen diversity peaks at intermediate stand ages with highest diversity in mixed‐wood stands. Our findings of distinct macrolichen communities supported by each age class and overstorey compositional type suggest that conservation of epiphytic macrolichen diversity would require forest managers to maintain a diverse age structure and overstorey composition in forest landscapes.
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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 | 0.000 | 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 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".