Nearshore microbial communities of the Pacific Northwest coasts of Canada and the U.S.
Bibliographic record
Abstract
A survey of marine pelagic coastal microbial communities was conducted over a large geographic latitude range, from Cape Mendocino in northern California USA to Queen Charlotte Sound in British Columbia Canada, during the spring to summer transition. DNA metabarcoding and flow cytometry were used to characterize microbial communities. Physical and chemical oceanography indicated moderate conditions during the survey with no widespread upwelling, marine heat wave, or other extreme conditions. However, four locations displayed features approaching acidified conditions: Heceta Head, Newport, Copalis Beach, and Cape Flattery. Although bacterial and archaeal communities at the Juan de Fuca canyon and northward had high similarity, those south of the Juan de Fuca canyon were well differentiated from each other. In contrast, eukaryotic microbial communities exhibited stronger geographic differentiation than bacterial and archaeal communities across the extent of the survey. Seawater parameters that were best predictors of bacterial and archaeal community structure were temperature, pH, and dissolved inorganic nutrients (nitrate, phosphate, silicate), while those that were best predictors of eukaryotic microbial community structure were salinity, dissolved oxygen, total alkalinity, and dissolved inorganic nutrients (nitrite, silicate). Although five bacterial and archaeal indicators for potentially corrosive waters were identified (Colwellia, Nitrosopumilus, Nitrosopelagicus, Sup05 cluster, Sva0996 marine group), no eukaryotic microbial indicators were found. Potentially pathogenic taxa detected in the survey included four disease-causing bacteria for mammals, finfish, and/or shellfish (Coxiella, Flavobacterium, Francisella, Tenacibaculum), sixteen genera of microalgae capable of producing biotoxins, and fifteen parasitic species. This study demonstrates the value of coordinating microbial sampling and analysis with broad-scale oceanographic surveys to generate insights into community structures of these important pelagic trophic levels.
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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 | 0.004 |
| Science and technology studies | 0.002 | 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".