IrIsh Forestry 41 The macrofungal component of biodiversity in
Bibliographic record
Abstract
Sitka spruce (Picea sitchensis (Bong.) Carr.) is the most commonly planted tree species in Ireland, with future increases in the area of Sitka spruce forests planned. In recent years the biodiversity of Sitka spruce plantations in Ireland has become a topic of much research interest. However, fungal biodiversity has yet to be systematically surveyed in Irish Sitka spruce forests. This study\treports\ton\tthe\tdiversity\tof\tmacrofungi\tfrom\tnine\tSitka\tspruce\tplots\tin\tfive\tcounties surveyed over three years. One hundred and forty four species were discovered in the plots, including three species new (previously unrecorded) to the Republic of Ireland. Over half the species discovered were ectomycorrhizal species, highlighting the generalist nature of Sitka spruce as an ectomycorrhizal host in Western Europe. The 10 most common species are listed; members of the genus Mycena were the most commonly found macrofungi. On a relative sampling basis (species per m2), the biodiversity of macrofungi in Irish Sitka spruce forests is comparable to that found in native Sitka spruce forests in Canada. The ability of Sitka spruce forests in Ireland to support native biodiversity is discussed with reference to studies of other taxonomic groups and recommendations for the promotion of fungal diversity in Irish Sitka spruce forests are made.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".