Phytoplankton ecology of a culturally eutrophic embayment: Hamilton Harbour, Lake Ontario
Bibliographic record
Abstract
Hamilton Harbour is a chronically eutrophic embayment located at the western end of Lake Ontario that has experienced many decades of agricultural, industrial, and urban contamination. It has been identified as an Area of Concern under the terms of the Great Lakes Water Quality Agreement between Canada and the United States. This study examines the ecology of the phytoplankton communities at one centrally located station during the ice-free period (May–October) of three non-consecutive years: 2002, 2004 and 2006. This was the first comprehensive study to be conducted since the 1970s. It was found that the phytoplankton communities are diverse and fluctuate throughout the year, along with changing nutrient, physical and environmental conditions. No consistent patterns of seasonal succession were observed throughout the study. Phytoflagellates including Cryptophyceae and Dinophyceae had a tendency to outnumber and out-compete other phytoplankton since they are mobile and able to seek out optimal habitats within the water column. For a highly eutrophic water body, algal biomass (annual mean ≈ 2.0 g m−3) was lower than expected and more consistent with mesotrophic conditions–an observation first made by researchers in the 1970s and attributed to the highly variable physical environment. While our study supports these earlier results, we also conclude that zooplankton grazing likely has a significant role in limiting the size of the algal standing crop. Several algal bloom events were captured during our study. In addition to the somewhat predictable blooms of Diatomeae in the spring and Cyanophyta in the summer, we also observed blooms of Cryptophyceae and Dinophyceae. In one case we observed a bloom with no dominant taxon–it contained a diverse mixture of Cryptophyceae, Euglenophyta and Dinophyceae–challenging the commonly held notion that algal blooms are essentially monocultures. Our results show that such a variable and stressed ecosystem requires frequent sampling to capture the rapid changes that occur.
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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 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| 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".