Interannual variability in trophic status of shallow lakes on the Boreal Plain: Is there a climate signal?
Bibliographic record
Abstract
We explored relations between climate and trophic status of shallow lakes (lake area > 5 ha, mean depth < 3.2 m) located on the subhumid western Boreal Plain of Canada. Correlation and regression analyses were used to assess the association between indicators of climate and satellite‐based estimates of trophic status (chlorophyll a (Chl a)). Chl a was derived using red band reflectance of Landsat satellite images for 76 lakes, which were then averaged for each year to produce a landscape median for summer (August) over a 20‐year period from 1984 and 2003. Our results showed that climate was related to interannual changes in trophic status. Average May temperature was positively correlated to Chl a, suggesting the importance of conditions in the early part of the growing season. Growing season effective precipitation (P – PET) was negatively correlated to Chl a such that wetter conditions seemed to lead to a dilution of Chl a. Very wet years resulted in a larger Chl a drop than one expected by a linear model, suggesting greater water contribution from the landscape. P – PET explained 64% of the variance in Chl a using a nonlinear regression tree. Our study offers clues as to how shallow lake systems may behave on the subhumid Boreal Plain as a function of future climate change.
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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 | 0.001 |
| 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 | 0.000 |
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".