Conservation of a transboundary lake: Historical watershed and paleolimnological analyses can inform management strategies
Bibliographic record
Abstract
International cooperation between Canada and the United States is necessary to sustain water quality and quantity of numerous cross-border water bodies. We used Lake Memphremagog as a case study for highlighting how paleolimnological and historical research can be insightful in developing conservation plans for transboundary waters. To investigate how the lake and its phosphorus (P) input from agricultural activity in the watershed have changed over the past ∼100 years, we developed decadal-scale, diatom-based records from analyses of sediment cores taken from the south and northwest ends of the lake and calculated watershed agricultural P budgets from Canadian and US agricultural census data. Based on these analyses, we observed substantial changes in diatom flora over the past century, and our diatom-based P transfer function demonstrated that lake trophic state in both basins has substantially varied. Correlation analyses between our diatom-inferred P concentrations and watershed P budgets identified agricultural inputs of P as a significant driver of lake trophic state, particularly from the 1930s to the 1970s. Recent dynamics in lake-water P concentrations are no longer tracking agricultural P budgets; instead, they likely reflect P arising from urban activities and possibly the slow release of P that previously accumulated in watershed soils or lake sediments. Given the complex network of regulatory agencies responsible for Lake Memphremagog and its watershed, as well as lessons learned from a neighboring transboundary lake, we predict that future lake management will be most effective if collaborations among local conservation groups and regional to national government agencies are fostered.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".