Exploring diatom diversity through cultures - a case study from the Bow River, Canada
Bibliographic record
Abstract
Diatom cultures can help answer taxonomic, biogeographic and ecological questions on a local and global scale. Unialgal cultures are derived from a single cell and provide abundant material for morphological and molecular analyses. The link between the historic morphological species concept and the molecular data is becoming increasingly important with the use of eDNA metabarcoding. Additionally, cultures provide insights into the life cycle of diatoms and thereby complement taxonomy and species ecology. In this study, we present an approach to extract benthic diatoms from an environmental sample to generate unialgal cultures. We explored diatom diversity in preserved assemblages and by culturing as many different taxa as possible from benthic freshwater samples taken on the same day from the Bow River in Calgary, Canada. With both methods we found a total of 221 different benthic diatom taxa, of which 182 were identified in the preserved diatom assemblages. Interestingly, an additional 39 taxa only appeared in the cultures. In total 129 strains were cultivated representing 71 different taxa. This study includes pictures of living cells demonstrating the additional merits of unialgal cultures, as they provide information on plastid details, auxospores and endosymbionts. Both, the identification of the diatom assemblages and the generation and identification of strains provide the foundation for additional water quality assessment tools, taxonomic insights and molecular references libraries.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".