Red-listed and indicator lichens in woodland key habitats and production forests in Sweden
Bibliographic record
Abstract
There are ca. 70 000 "woodland key habitats" (WKHs) in Sweden that according to definition should contain red-listed species, but their species content is seldom known. Indicator species are used as one tool to identify the WKHs. In two areas in southern Sweden red-listed and indicator lichen species were surveyed in line transects in a total of 25 WKHs (45 ha) and, for comparison, in 74 ha of surrounding production forest. Altogether 19 red-listed species, representing ca. 25% of the Swedish Red List forest lichen species so far recorded from the study areas, and 35 indicator species were found. Ninety-five percent of all records were epiphytic. The most evident result from this study was the large difference in the number of species records in the production forests between the two study areas. In contrast, the WKHs in both areas had a similar number of species records. The WKHs were expected to be significantly richer than the production forests in regard to the occurrence of indicator and red-listed species, but this was only found to be true in one of the areas. In both areas there was a tendency for the rarest red-listed species to be confined to the WKHs. Nestedness and correlation analyses suggested that Arthonia vinosa was a relevant indicator of red-listed lichens; however, Calicium parvum was found to be inappropriate as an indicator species. It is concluded that at the regional scale the production forest can host considerable amounts of indicator and red-listed lichen species but that the WKHs are important for the preservation of rare lichens.
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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".