Diversity of<i>Ramalina sinensis</i>and its photobiont in local populations
Bibliographic record
Abstract
Abstract Ramalina sinensisis a widespread lichen in the Northern Hemisphere with sparse local populations, and its potential to adapt to changing environmental conditions is unknown. The objectives of this study were to determine whether geographical distance reflects fungal phylogenetic patterns, and to infer algal identity and its pattern of geographical distribution. Twenty-three samples ofR. sinensiswere collected from three geographical regions in Manitoba. The internal transcribed spacer of ribosomal DNA (ITS rDNA) was sequenced from each of the algal and fungal partners, and phylogenetic analyses were performed. Algal haplotypes were estimated and placed on a map of the geographical regions. Although the fungal partner showed no geographical segregation within Manitoba, the divergence of three samples added to the phylogeny from GenBank suggested that a pattern may be evident if broader geographical distances were examined. The photobiont sequence was determined to be most similar to that ofTrebouxia impressaandT. potteri,two widely distributed algal species. The algal partner showed no geographical structure with sequence polymorphism or haplotype analyses. The abundance of sexual reproduction might explain widespread occurrence and the absence of geographical segregation of the fungus. This study suggests that the diversity in each of the symbionts ofR. sinensisshould not be a limiting factor for adaptation.
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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 | 0.001 | 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) | 0.001 | 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".