Global distribution of cyanobacterial ecotypes in the cold biosphere
Bibliographic record
Abstract
Perennially cold habitats are diminishing as a result of climate change; however, little is known of the diversity or biogeography of microbes that thrive in such environments. Here we use targeted 16S rRNA gene surveys to evaluate the global affinities of cold-dwelling cyanobacteria from lake, stream and ice communities living at the northern limit of High Arctic Canada. Pigment signature analysis by HPLC confirmed the dominance of cyanobacteria in the phototrophic communities of these High Arctic microbial mats, with associated populations of chlorophytes and chromophytes. Microscopic analysis of the cyanobacteria revealed a diverse assemblage of morphospecies grouping into orders Oscillatoriales, Nostocales and Chroococcales. The 16S rRNA gene sequences from six clone libraries grouped into a total of 24 ribotypes, with a diversity in each mat ranging from five ribotypes in ice-based communities to 14 in land-based pond communities. However, no significant differences in composition were observed between these two microbial mat systems. Based on clone-library and phylogenetic analysis, several of the High Arctic ribotypes were found to be >99% similar to Antarctic and alpine sequences, including to taxa previously considered endemic to Antarctica. Among the latter, one High Arctic sequence was found 99.8% similar to Leptolyngbya antarctica sequenced from the Larsemann Hills, Antarctica. More than 68% of all identified ribotypes at each site matched only cyanobacterial sequences from perennially cold terrestrial ecosystems, and were <97.5% similar to sequences from warmer environments. These results imply the global distribution of low-temperature cyanobacterial ecotypes throughout the cold terrestrial biosphere.
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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 | 0.001 |
| 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) | 0.001 | 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".