Contrasting Impacts of Agricultural Intensification and Urbanization on Lake Phosphorus Cycling and Implications for Managing Eutrophication
Bibliographic record
Abstract
Abstract Sediment core and water quality data, together with historical information on land use/land cover (LULC), were used to reconstruct changes in phosphorus (P) loading and cycling in Lake Wilcox, Ontario, Canada, since the early 1920s. After first being cleared for farming, the originally forested watershed subsequently underwent urbanization. The large increase in P loading accompanying agricultural intensification after World War II caused the eutrophication of the lake. However, improved soil conservation since the 1980s and urban stormwater management since the 1990s have brought watershed P loading and sediment accumulation down to levels comparable to the early 1900s. Yet, the lake continues to exhibit eutrophication‐like symptoms, especially the intensification of hypoxia in the hypolimnion. Post‐2000 water quality data indicate that the latter is not driven by external P loading from the watershed, but rather by rapid salinization that strengthens the lake's summer stratification and enhances internal P loading. Salinization is caused by the increasing application of deicing agents in the expanding urban area. Curbing salt inputs will therefore be essential to restore the lake. Overall, our results provide new insights into the shifts in lake biogeochemistry associated with LULC changes and the implementation of best management practices. The approaches and findings of our case study have broad applicability for the large number of freshwater ecosystems worldwide that are experiencing salinization.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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 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".