Modelling effects of nutrients and hypoxia on Lake Erie's central basin foodweb
Bibliographic record
Abstract
Abstract Hypoxia (dissolved oxygen <2 mg l-1) has long been a prevalent feature of the central basin of Lake Erie. Studies of the sublethal impacts of hypoxia on fishes have focused on individual species feeding rates, behavior and spatial distributions over short time periods, but the long-term effects on the fish community and its foodweb are poorly known. Sublethal effects of hypoxia on fish include: interrupting their vertical migration, displacing them from bottom habitats either up into the water column or away from the hypoxic zones, altering predator-prey relationships by segregation or aggregation of predators and their prey, and increasing fishing mortality by concentrating fish at the edge of hypoxic zones. We used the Ecopath with Ecosim foodweb model to investigate the singular and combined effects of nutrient concentration and hypoxia on the foodweb structure in Lake Erie's central basin. Our model tracked predator-prey interactions and population biomass of 33 model groups. We balanced the model in Ecopath and calibrated it against biomass time series data from 1996 up to 2020. Model simulations were run with varied nutrients (from 20 to 220% of the previous nutrient loading target level) and hypoxia (none, average summer value from 1996 to 2017, historical high) as forcing variables on the foodweb. Model results suggested that nutrients had positive, non-linear effects on foodweb biomass, while hypoxia decreased biomass of benthos, benthivorous fishes, and some omnivores, but increased biomass of plankton and planktivorous fishes. Nutrient effects were greater than hypoxia effects on the foodweb. Results of the foodweb model analysis may inform water quality and fisheries management strategies for Lake Erie's central basin.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 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 | 0.001 |
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 teacher head, 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".