Corticolous bryophytes in managed Douglas-fir forests: habitat differentiation and responses to thinning and fertilization
Bibliographic record
Abstract
Corticolous bryophytes, that is, mosses and liverworts that inhabit tree trunks, represent an important component of plant diversity in temperate ecosystems, but little is known of their ecology in managed forests. In this study, we quantified community composition and habitat differentiation of corticolous bryophytes in Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) plantations subjected to experimental thinning and fertilization treatments. Twenty-four bryophyte species were recorded in a sample of 480, 225 cm2 quadrats on 60 tree trunks. All moss species and obligately epiphytic liverworts (those with a primary habitat preference for tree trunks) showed highest cover values on south and west exposures. In contrast, facultatively epiphytic liverworts occurred only at the tree base, and mainly on north and west exposures. Pairwise correlations among species cover values were nearly always positive, and cover of the most abundant species, Isothecium myosuroides, was also positively correlated with local species richness of other bryophyte taxa. These patterns suggest that competitive interactions among bryophyte species are not strong in this community. There was little evidence for fertilization or thinning effects on total bryophyte cover or species richness. However, analyses of community composition and species-specific responses indicated significant negative effects of thinning on some bryophyte species. Observed patterns of habitat differentiation, interspecific associations, and treatment responses suggest that stand hydrology and microclimate are of primary importance in determining the distribution and abundance of corticolous bryophytes in managed forests.Key words: corticolous bryophytes, liverworts, mosses, nitrogen fertilization, plant diversity, silvicultural thinning.
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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".