Long-Term Changes of Hypolimnetic Dissolved Oxygen and Phytoplankton Community Composition in a Large Lake, Lake Simcoe, Ontario and Revisit Dissolved Oxygen Profile Models for Lakes in Central Ontario
Bibliographic record
Abstract
Long-term changes in volume-weighted hypolimnetic dissolved oxygen (VWHDO) and phytoplankton community composition were examined as important water quality indicator in Lake Simcoe, a large freshwater lake with impacts by various drivers such as dreissenid mussel (DM) invasion, reduction in phosphorus (P) loading and climatic change and oscillations. VWHDO dynamics were examined by several multiple linear regressions which revealed that VWHDOmin was positively correlated with the invasion of DM and negatively correlated with hypolimnetic water temperature; VWHDO depletion rate (DR) was positively correlated with ammonia and total phosphorus (TP) annual loading. Hence, longer period of thermal stratification (L) may have offset improvements in VWHDOmin generated by P controls and invasive species. Redundancy analysis and variation partitioning revealed that DM acted on phytoplankton composition indirectly by changing the environmental conditions because environmental variables and DM individually explained little variance in phytoplankton composition but water chemistry variables and DM collectively explained a large portion of the variation. \nA series of models predicting the uppermost plane of the DO-depleted zone (Zox), spring dissolved oxygen (DOi) profile and end-of-summer dissolved oxygen (DOf) profile built by Molot et al. (1992) were re-analyzed, re-calibrated with more recent data (A lakes during 1990-2013), and validated (B lakes during 1990-2013). With the current brownification trend (increased DOC), we expected to see increased DOf at all depths; however, increased reduced N species (ammonia) in the hypolimnion would offset the brownification effect.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".