Glacier-fed stream diatoms (Bacillariophyta) from the Rwenzori Mountains, Uganda, with the description of one new species from the genus <i>Neidium</i>
Bibliographic record
Abstract
Glacier-fed streams (GFSs) are harsh environments hosting unique, highly specialized communities. Interestingly, glaciers and their GFSs are also present in Earth’s tropical regions, where environmental characteristics contrast with GFS conditions elsewhere. Yet, despite the unique and isolated nature of tropical GFSs, little is known about their inhabitants, even though they may disappear later this century with ongoing climate change. Here, we examined diatom communities from one of the last tropical African GFSs in the Rwenzori Mountains, Uganda, to characterize the composition and diversity of this unique system. Six sediment-associated biofilm samples were collected from two reaches of a stream draining the Mt. Stanley Glacier, and the resident diatom communities were studied morphologically using light and scanning electron microscopy, as well as through the sequencing of amplicons from extracted DNA (18S and rbcL). In general, morphological results agree well with barcoding results, but each individually provides irreplaceable insights. In total, we identify 24 morphotypes utilizing light microscopy, 101 diatom Amplicon Sequence Variants (ASVs) using 18S sequences, and 65 ASVs with rbcL. Across approaches, common genera include Achnanthidium, Psammothidium, Neidium, Cymbopleura, Eunotia, and Pinnularia. However, only about half of the diversity could be assigned to the species level across methodologies, including several of the most common taxa, indicating a high level of uniqueness. Accordingly, one of the most common taxa encountered is described here as a new species, Neidium rwenzoriense sp. nov. Our results emphasize the Rwenzori Mountains as a global hotspot for endemism, and the novelty of disappearing tropical GFSs as diatom habitats.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".