Watershed Land Use Controls on Chemical Inputs to Lake Ontario Embayments
Bibliographic record
Abstract
There is considerable interest in understanding the role of land use in controlling surface water quality. This study was conducted to assess the role of land cover in regulating temporal and spatial patterns in nutrients and major solutes in rivers that drain into Lake Ontario. Water samples were collected monthly from 22 river sites in subwatersheds of eight embayments along the New York coast of Lake Ontario over the period 2001-2003. Samples were analyzed for nutrients and major solutes. The land cover of the subwatersheds was varied, but largely a mixture of forest and agricultural lands. Rivers draining largely agricultural lands exhibited distinct seasonal patterns, particularly for nutrients. Nitrate and total nitrogen (TN) concentrations were generally low during the summer growing season, increased markedly during fall and decreased during winter and spring. Total phosphorus (TP), dissolved organic carbon (DOC), and most ion (Na(+), K(+), Ca(2+), Mg(2+), Cl(-), SO(4)(2-)) concentrations varied with seasonal discharge patterns. Distinct spatial patterns were observed in river solute concentrations that closely corresponded with land use. Solute concentrations increased markedly with increases in the percentage of the watershed occurring as agricultural lands. Such a pattern has been commonly observed for nutrients (e.g., TP, TN, NO(3)(-)), but this relationship was also evident for most non-nutrient solutes (e.g., DOC, Ca(2+), F(-), SO(4)(2-)), a pattern which has not previously been reported. These observations suggest that agricultural activities mobilize most major elements, enhancing transport across the temperate landscape and impacting downstream water resources, including embayments and the Lake Ontario ecosystem.
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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 | 0.000 | 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 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".