Effects of ocean acidification on the growth, photosynthetic performance, and domoic acid production of the diatom Pseudo-nitzschia australis from the California Current System
Bibliographic record
Abstract
Pseudo-nitzschia australis (Frenguelli), a toxigenic pennate diatom capable of producing the neurotoxin domoic acid (DA), was examined in unialgal laboratory cultures to quantify its physiological response to ocean acidification (OA) - the decline in pH resulting from increasing partial pressure of CO2 (pCO2) in the oceans. Toxic blooms of P. australis are common in the coastal waters of eastern boundary upwelling systems (EBUS), including those of the California Current System (CCS) off the west coast of the United States where increased pCO2 and decreased seawater pH are well-known. This study determined the production of dissolved (dDA) and particulate DA (pDA), the rates of growth and nutrient (nitrate, silicate and phosphate) utilization, cellular elemental ratios of carbon and nitrogen, and the photosynthetic response to declining pH during the exponential and stationary growth phases of a strain of P. australis isolated during a massive toxic bloom that persisted for months along much of the U.S. west coast during 2015. Our controlled lab studies showed that DA production significantly increased as pCO2 increased, and total DA (pDA + dDA) normalized to cell density was 2.7 fold greater at pH 7.8 compared to pH 8.1 (control) during nutrient-limited stationary growth. However, exponential growth rates did not increase with declining pH, but remained constant until pH of 7.8 was reached, and then specific growth rates declined by ca. 30%. The toxin results demonstrate that despite minimal effects of OA observed during the nutrient-replete exponential growth phase, the enhancement of DA production, notably the 3-fold increase in particulate DA per cell, with declining pH from 8.1 to 7.8 during the nutrient-depleted stationary phase, supports the hypothesis that increasing pCO2 will result in greater toxic risk to coastal ecosystems from elevated ambient concentrations of particulate DA. The ecological consequences of decreasing silicate uptake rates and increasing cellular carbon quotas with declining pH may potentially ameliorate some negative impacts of OA on Pseudo-nitzschia growth in natural systems.
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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".