Sensitivity of physical lake processes to climate change within a large Precambrian Shield catchment
Bibliographic record
Abstract
Abstract Potential future changes in lake physical processes (e.g. stratification and freezing) can be assessed through exploring their sensitivity to climate change, and assessing the current vulnerability of different lake types to plausible changes in meteorological drivers. This study quantifies the impacts of climate change and sensitivity of lake physical processes within a large (5100 km 2 ) Precambrian Shield catchment in south‐central Ontario. Historic regional relationships are established between climate drivers, lake morphology, and lake physical changes through generalized linear modelling (GLM), and are used to quantify likely changes in timing of ice phenology and lake stratification across 72 lakes under a range of future climate models and scenarios. In response to projections of increased temperature (ensemble mean of +3.3 °C), both earlier ice‐off and onset of summer stratification were projected, with later ice‐on and fall turnover compared to the baseline. Process sensitivity to climate change varied by lake type; shallower lakes with a smaller volume (less than 15 m deep and less than 0.05 km 3 ) were more sensitive to processes associated with lake heating (stratification onset and ice‐off), and deeper lakes with a larger surface area (greater than 30 m deep and greater than 1000 ha) were more sensitive to processes associated with lake cooling (fall turnover and ice‐on). These results indicate that whereas small lakes are vulnerable to climate warming because of changes that occur in spring and summer, larger lakes are particularly sensitive during the fall. The findings suggest that lake morphology and associated sensitivity should be considered in the development of sustainable lake management strategies. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.001 |
| 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".