Modelling phosphorus dynamics in Cootes Paradise marsh: Uncertainty assessment and implications for eutrophication management
Bibliographic record
Abstract
Cootes Paradise marsh, a hypereutrophic wetland draining into the western end of Hamilton Harbour, Ontario, has historically been considered an important regulatory factor of the severity of local eutrophication phenomena. In this study, we present a modelling exercise that aims to draw inference on the relative contribution of various external and internal flux rates to the phosphorus budget of Cootes Paradise. We first examined the capacity of a phosphorus mass-balance model, accounting for the interplay among water column, sediments and macrophytes, to reproduce the observed total phosphorus dynamics over a 17-year period (1996–2012). Water level fluctuations were one of the key challenges for balancing the phosphorus budget during model calibration. Our analysis shows that the model satisfactorily reproduced the average seasonal patterns, as well as the year-to-year total phosphorus variability (coefficient of determination = 0.20, relative error = 26.8%, root mean square error = 62.2 μg P l−1, model efficiency = 0.15). However, our model failed to capture two years of the study period (1997 and 2007), when ambient TP levels significantly deviated from the typically prevailing conditions. Model sensitivity analysis identified the sedimentation of particulate material and diffusive reflux from sediments as two critical processes to characterize the phosphorus cycle in the wetland. Based on the current parameter specification, our model postulates that the sediments still act as a net sink, whereas macrophyte processes (respiration rates, nutrient uptake from interstitial water) appear to play a minor role. We conclude by discussing the various sources of uncertainty and additional remedial actions required in Cootes Paradise marsh to realize a shift from the current turbid-phytoplankton dominated state to its former clear-macrophyte dominated state.
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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 | 0.000 |
| 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 | 0.000 |
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 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".