Long term water clarity changes in<scp>N</scp>orth<scp>A</scp>merica's<scp>G</scp>reat<scp>L</scp>akes from multi‐sensor satellite observations
Bibliographic record
Abstract
Abstract Water clarity in North America's Laurentian Great Lakes has undergone considerable change over the last several decades as a consequence of invasive species, eutrophication, and implemented nutrient management practices. Satellite observations from the CZCS, SeaWiFS, and MODIS‐Aqua sensors have been used in tandem with long term records of Secchi disk depth ( Z SD ) to provide a retrospective analysis of spatial and temporal variations in water clarity over the Great Lakes. A simple empirical algorithm is presented, relating Z SD to remote‐sensing reflectance at ∼ 550 nm ( R rs∼550 ). Results suggest remarkable and complex changes in water clarity over the Great Lakes. Lakes Ontario, Huron, and Michigan have seen increases in average Z SD over the three sensor periods of 58%, 49%, and 62%, respectively. Lake Erie shows highly variable Z SD with no consistent long term trends, while Lake Superior has remained fairly consistent in its lake‐wide water clarity conditions. Temporal trends document the decrease in whiting events on Lake Michigan while capturing the ongoing occurrence of these seasonal bright‐water events on Lake Ontario. Results indicate a divergence in Z SD trends between nearshore and offshore environments; with larger increases in offshore than nearshore Z SD and some nearshore areas suggesting a decrease in Z SD . Offshore regions of Lakes Huron, Michigan, and Superior show diminished Z SD seasonality in contrast to increasing seasonal variance in the nearshore. Spatial and temporal variations in Z SD are in agreement with documented reductions in Great Lakes bioproductivity, degrading nearshore water quality, and changing biogeochemical processes influencing whiting events and sediment resuspension.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".