Assessing population structure and host specialization in lichenized cyanobacteria
Bibliographic record
Abstract
Coevolutionary theory predicts that the distribution of obligately symbiotic organisms will be determined by the dispersal ability and ecological range of both partners. We examined this prediction for lichen-forming fungi that form obligate symbioses with cyanobacteria. We compared genotypes of both partners of 250 lichens collected at multiple spatial scales in British Columbia, Canada. Multilocus sequence data collected from a subset of 128 of the specimens were used to determine the degree of recombination within the cyanobacterial populations. We found that six distinct clusters of cyanobacterial genotypes are distributed throughout the known global phylogeny of the genus Nostoc, and that each appears to be evolving clonally. Fungal specialization is high, with each species associating with either one or two of the cyanobacterial clusters, while cyanobacterial specialization varies, with clusters associating with between one and 12 different fungal species. Specialization also varies geographically, with some combinations restricted to a single site despite the availability of both partners elsewhere. Photobiont association patterns are determined by a combination of genetically based specificity, spatial population structure, and ecological factors and cannot be easily predicted by photobiont dispersal syndromes.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".