Unusual Hemiaulus Bloom Influences Ocean Productivity in Northeast U.S. Shelf Waters
Bibliographic record
Abstract
Abstract. Ocean production and trophic transfer rates, including Net Community Production (NCP), Net Primary Production (NPP), Gross Oxygen Production (GOP), and microzooplankton grazing rates are key metrics for understanding marine ecosystem dynamics and impacts on biogeochemical cycles. Because of its temperate location and high dynamic range of environmental conditions and long-term human utilization, the long-term ecological research site in the coastal Northeastern U.S. Shelf (NES) of the Northwestern Atlantic Ocean offers an ideal opportunity to understand how productivity shifts in response to changes in planktonic community composition. While small phytoplankton usually dominate in the NES waters during the summer, a bloom of the large diatom genus Hemiaulus, with N2 fixing symbionts, was observed in the mid-shelf region during the summer of 2019. NCP was 2.5 to 9 times higher when Hemiaulus dominated compared to NCP throughout the same geographic area during the summers of 2020–2022. The Hemiaulus bloom in summer 2019 also coincided with higher trophic transfer efficiency from phytoplankton to microzooplankton, higher GOP and NPP, and higher sea surface temperatures than summers 2020–2022. This study shows that the presence of an atypical phytoplankton community that alters the typical size distribution of the primary producers can greatly influence productivity and trophic transfer, highlighting the dynamic nature of the coastal ocean. Notably, summer 2018 NCP levels were also high although no atypical phytoplankton community was present. A better understanding of the dynamics of the NES in terms of biological productivity is of primary importance, especially in the context of changing environmental conditions due to climate processes.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".