Assessing hypolimnetic oxygen concentrations in Canadian Shield lakes: Deriving management benchmarks using two methods
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The ability to predict hypolimnetic dissolved oxygen concentrations in lakes and to track changes in concentrations over time in response to known environmental stressors is critical for effective lake management. The background concentrations of deepwater oxygen, in particular, provide important management benchmarks for assessing the impact of current and future shoreline residential development on water quality. Background can be defined as the conditions that exist in the absence of, or prior to, human influence. We compare 2 models commonly used to predict end-of-summer, volume-weighted hypolimnetic oxygen (VWHO) concentrations in Canadian Shield lakes. The paleoecological and empirical models are evaluated in their ability to predict present-day VWHO concentrations, and then compared in their predictions of background VWHO concentrations and in predictions of changes in VWHO from background to present-day conditions. The predictive power of the 59-lake paleoecological model (jackknifed r2 = 0.51, RMSEP = 2.18 mg/L) is comparable to other models that have used chironomids to predict the degree of hypolimnetic anoxia in lakes but is lower than that produced by the empirical modelling approach (r2 = 0.87, SE = 1.04 mg/L). However, this discrepancy may be offset by the enhanced realism of the paleoecological model, including its ability to predict declines in VWHO over time. The combined use of the paleoecological and empirical modelling approaches may allow lake managers to examine changes in deepwater oxygen concentrations in response to a single “targeted” stressor (e.g., residential shoreline development) and to multiple environmental stressors (e.g., climate change, hydrological management).
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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) | 0.001 | 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 it