The eukaryome of modern microbialites reveals distinct colonization across aquatic ecosystems
Bibliographic record
Abstract
Abstract Microbial diversity includes bacteria, archaea, eukaryotes, and viruses; however, protists are less studied for their impact and diversity within ecosystems. Protists have been suggested to shape the emergence and decline of ancient stromatolites. Modern microbialites offer a unique proxy to study the deposition of carbonate by microbial communities due to analog status for ancient ecosystems and their cosmopolitan abundance. We examined protists across aquatic ecosystems between freshwater (Kelly and Pavilion Lake in British Columbia, Canada) and marine microbialites (Shark Bay, Australia and Highborne Cay, Bahamas) to decipher the transition with respect to diversity and composition. While factors such as sequencing technology and primer-bias might influence our conclusions, we found that at the taxonomic compositional-level, the freshwater microbialite communities were clearly distinct from the marine microbialite communities. Chlorophytes were significantly more abundant in the freshwater microbialites, while saltwater microbialites communities were primarily composed of pennate diatoms. Despite the differences in taxonomic make-up, we can infer the convergent important role of these protists to microbialite community health and function. These results highlight not only the consistency and potential role of microbialite eukaryotic communities across geographic locations, but also that other factors such as salinity seem to be the main drivers of community composition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".