A Molecular Survey of <i>Ulva</i> (Chlorophyta) in Temperate Australia Reveals Enhanced Levels of Cosmopolitanism
Bibliographic record
Abstract
The green algal genus Ulva includes a speciose group of marine macroalgae inhabiting shallow seas worldwide. Although algal blooms in Asia highlight the opportunistic nature of several "nuisance" species, recent research clearly reveals important positive benefits of Ulva. Applied research requires accurate, reliable, and rapid identification, however, identification of Ulva spp. has met with con-siderable difficulty. Consequently, many have turned to molecular markers to aid in taxonomy. Previous studies of plants and algae have relied heavily on ITS and rbcL. Recently, tufA has been presented as a suitable barcoding gene to facilitate species-level identification of green macroalgae and it is used here to explore the diversity of Ulva spp. in temperate Australia. Ninety Ulva specimens collected from 38 sites across five states were sequenced for this gene region with exemplars from each genetic group also sequenced for rbcL to test for congruence. Collections of Australian Ulva spp. were compared to samples from Asia and North America and exhibited trends consistent with recent studies in terms of species relationships. Results support an overwhelmingly cosmopolitan flora in temperate Australia that contrasts with other Australasian surveys of Ulva that report a greater number of endemics and new species. Four new records, as well as numerous range extensions for taxa already known from the country, are documented. Evidence for three nonindigenous Ulva species in temperate Australia is discussed.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".