A DNA barcode examination of the red algal family Dumontiaceae in Canadian waters reveals substantial cryptic species diversity. 1. The foliose <i>Dilsea</i>–<i>Neodilsea</i> complex and <i>Weeksia</i>This paper is one of a selection of papers published in the Special Issue on Systematics Research.
Bibliographic record
Abstract
The field of DNA barcoding is working towards generating a genetic system for the quick and accurate identification of eukaryotic species. For the more systematic minded, however, DNA barcoding offers a new approach towards screening and uniting large numbers of biological specimens in genetic groups as a first step towards assigning them to species and genera in an approach best termed “molecular-assisted alpha taxonomy”. This approach is particularly amenable in organisms with simple morphologies, a propensity for convergence, extensive phenotypic plasticity, and life histories with an alternation of heteromorphic generations. It is hard to imagine a group of organisms better defined by all of these traits than the marine macroalgae. In an effort to assess the utility of the DNA barcode (COI-5′) for testing the current concepts of biodiversity of marine macroalgae in Canada, a study to assess species diversity in the red algal family, Dumontiaceae, was initiated. Through this work I confirm the presence in Canadian waters of Dilsea californica (J. Agardh) Kuntze, Dilsea integra (Kjellman) Rosenvinge, and Neodilsea borealis (I.A. Abbott) Lindstrom of the Dilsea–Neodilsea complex, and Weeksia coccinea (Harvey) Lindstrom for the genus Weeksia . However, our work has uncovered two additional species of the former complex, Dilsea lindstromiae Saunders sp. nov. and Dilsea pygmaea (Setchell) Setchell, and an additional species of the latter, Weeksia reticulata Setchell, effectively doubling representation of these foliose dumontiacean genera in Canadian waters.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".