Assigning morphological variants of <i>Fucus</i> (Fucales, Phaeophyceae) in Canadian waters to recognized species using DNA barcoding
Bibliographic record
Abstract
The intertidal brown algal genus Fucus (Phaeophyceae) consists of individuals with a generally dichotomously branched habit. Morphological variability within species, combined with morphological similarity between species, renders field identification difficult. In light of recent taxonomic revisions, which reduced 10 taxa traditionally recognized in Canada to four species, we tested the utility of the DNA barcode (mitochondrial cytochrome oxidase 1, 5′) for assigning individuals to these species. We sequenced the DNA barcode for 125 specimens representing all morphologies recognized. We confirmed our results by sequencing the internal transcribed spacer region for 66 specimens. This is the first study to establish that the DNA barcode successfully assigns different morphologies of brown algae to known species as well as other single-gene molecular markers currently used. Furthermore, the results uncovered substantial phenotypic plasticity in Pacific Fucus distichus , from moss-like fragments embedded in estuarine mud, strap-like morphs on exposed rocky coasts, to “spiralis”-like morphs in the upper intertidal whereas phenotypic expression for this species was more restricted in the Atlantic.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| 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".