Environmental conditions and phytoplankton dynamics associated with Pseudo-nitzschia abundance and domoic acid in the Juan de Fuca eddy
Bibliographic record
Abstract
The Juan de Fuca eddy, located off the coasts of Washington (USA) and British Columbia (Canada), has been identified as a region that frequently contains relatively high levels of domoic acid (DA), a toxin produced by some members of the marine diatom genus, Pseudo-nitzschia. This seasonal eddy provides a unique environment to study the influence of nutrients on Pseudo-nitzschia abundance and DA accumulation in the field. Vertical sampling in the Juan de Fuca region was conducted in May, July and September of 2001 in an effort to determine environmental conditions and phytoplankton dynamics within the eddy compared to surrounding waters. The eddy was characterized by high primary productivity and high biomass in May and September relative to surrounding waters and was dominated by diatoms in the > 5 μm size-fraction. In May, nitrate (NO3-) concentrations and the corresponding NO3- assimilation rates by phytoplankton within the eddy surface waters were relatively low. In contrast, in September, NO3- was high and NO3- assimilation rates increased by 7 times relative to those in May. DA was below detection levels at all stations in May and July. In September, Pseudo-nitzschia reached highest cell densities (∼2 × 104 cells l-1) and particulate DA (∼30 ng DA equivalents l-1) was detected in surface waters of the eddy. The presence of DA in healthy growing phytoplankton communities indicates a need to examine other environmental conditions that induce DA production in natural Pseudo-nitzschia populations than have previously been reported in nutrient-stressed laboratory studies.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".