Impact of Surface Temperature and Salinity on the Ratio of Marine Diatoms to Dinoflagellates in the Trevor Channel Area
Bibliographic record
Abstract
In an effort to illuminate the factors that influence surface phytoplankton community composition with respect to marine diatoms (Class Bacillariophyceae) and dinoflagellates (Phylum Dinoflagellata), temperature and salinity data were collected. Phytoplankton samples were collected at six surface water locations along the Trevor channel near Bamfield, British Columbia where sampling locations were of known gradients of salinity and temperature. Each sample was analysed under a light microscope, where 2 µL volumes of seawater were counted for both dinoflagellate and diatom abundances. The ratio of diatoms to dinoflagellates was determined by averaging multiple counts of well-mixed samples from each station. Surface temperature and salinity data were collected using individual CTD (Conductivity, Temperature, Depth) casts, where only the surface values were considered. The phytoplankton ratios were then correlated to each of temperature and salinity. It was found with strong positive correlation that conditions with higher salinity favoured dinoflagellate-dominant communities (r = 0.97, p = 0.00013) and conditions with higher temperature favoured diatom-dominant communities (r = 0.92, p = 0.0035). This data may prove useful in studies regarding how small and large scale climatic changes affect phytoplankton community composition, and proves interesting directions in research as to how bottom-up controls on community structure can impact abundances of macro-organisms.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".