Factors affecting Cladophora growth in the eastern basin of Lake Erie: Analysis of a monitoring dataset (2012–2019)
Bibliographic record
Abstract
Cladophora is a naturally occurring benthic alga in the Great Lakes which can reach nuisance levels in the nearshore, leading to beach closures and other impacts. A monitoring program was initiated in 2012 in the eastern basin of Lake Erie to identify ecological factors driving its growth. Inflows from the Grand River, the largest river to the north shore, were generally positively associated with phosphorus concentrations in the nearshore and negatively associated with light reaching the lakebed. At the depths sampled (3 m–18 m), Cladophora was strongly influenced by light availability, and due to shading by the Grand River plume, an overall negative association was found between Cladophora biomass and phosphorus inputs. Phosphorus limitation was only observed at shallow sites farthest from the Grand River. Positive associations between dreissenid mussel coverage and both Cladophora biomass and tissue phosphorus suggest that nutrient cycling by dreissenids supports Cladophora growth. Our results indicate that i.) the Grand River has a strong influence on nearshore nutrient levels and water clarity; and ii.) Cladophora is limited by both phosphorus and light to varying degrees within the study area, although light appears to be the dominant factor, at least at these depths, years, and locations. The implication that phosphorus reductions could lead to increased Cladophora biomass by improving light conditions will need to be considered carefully against the known historical success of controlling nuisance algae through nutrient management.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".