Forestcheck: the response of lichens and bryophytes to silviculture in jarrah (<i>Eucalptus marginata</i>) forest
Bibliographic record
Abstract
Summary The effect of silvicultural treatments on lichen, moss and liverwort communities was investigated as a component of the FORESTCHECK monitoring project in jarrah forest of south-west Western Australia. Forty-eight monitoring grids were established across five locations within four jarrah forest ecosystems and were monitored over a 5-y period, with one location monitored each year. Silvicultural treatments (shelterwood/selective cut and gap release) were compared with reference forest that had never been harvested or had not been harvested for over 40 y. A total of 318 species was recorded comprising 280 lichens, 27 mosses, 10 liverworts and one hornwort. Seventy-two percent were identified to species level. There were strong regional influences (relating to different forest ecosystem types) observed in the composition of cryptogam communities. Silvicultural treatments significantly affected the species richness of lichens, which decreased with intensity of harvest, and the composition of the total cryptogam community. Total cryptogam species richness was lowest in silviculturally treated grids 1–4 y after treatment, but 10 or more years after treatment it was similar to that in reference grids prescribed-burnt 10 y or more previously. Species such as Sematophyllum subhumile var. contiguum (moss) and Cephaloziella exilifolia (liverwort) and several lichens were more frequent in reference forest than in silviculturally treated forest. Pannaparmelia wilsonii, Hypogymnia subphysodes and Tephromela alectoronica, two foliose and a crustose lichen associated with mature trees, were also recorded in the gap release treatment, demonstrating the importance of retained habitat trees for species other than native mammals and birds. One-half of all the cryptogams recorded used coarse woody debris as a substrate and 40% of them depended on it entirely. Coarse woody debris is affected by both timber harvesting and fire, so there is a need to learn more regarding the specific requirements of saproxylic cryptogams in jarrah forest.
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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 | 0.001 |
| 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".