Cox2 community barcoding at Prince Edward Island reveals long-distance dispersal of a downy mildew species and potentially marine members of the Saprolegniaceae
Bibliographic record
Abstract
Abstract Marine oomycetes are highly diverse, globally distributed, and play key roles in marine food webs as decomposers, food source, and parasites. Despite their potential importance in global ocean ecosystems, marine oomycetes are comparatively little studied. Here, we tested if the primer pair cox2F_Hud and cox2-RC4, which is already well-established for phylogenetic investigations of terrestrial oomycetes, can also be used for high-throughput community barcoding. Community barcoding of a plankton sample from Brudenell River (Prince Edward Island, Canada), revealed six distinct oomycete OTU clusters. Two of these clusters corresponded to members of thePeronosporaceae—one could be assigned toPeronospora verna, an obligate biotrophic pathogen of the terrestrial plantVeronica serpyllifoliaand related species, the other was closely related toGlobisporangium rostratum. While the detection of the former in the sample is likely due to long-distance dispersal from the island, the latter might be a bona fide marine species, as several cultivable species of thePeronosporaceaeare known to withstand high salt concentrations. Two OTU lineages could be assigned to theSaprolegniaceae. While these might represent marine species of the otherwise terrestrial genus, it is also conceivable that they were introduced on detritus from the island. Two additional OTU clusters were grouped with the early-diverging oomycete lineages but could not be assigned to a specific family. This reflects the current underrepresentation ofcox2 sequence data which will hopefully improve with the increasing interest in marine oomycetes.
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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".