Insights for lake management gained when paleolimnological and water column monitoring studies are combined: A case study from Baptiste Lake
Bibliographic record
Abstract
Many lakes within the Boreal Plain and Grassland regions of Canada are currently eutrophic to hypereutrophic. Limited paleolimnological work has been conducted to define water quality trajectories of lakes within this region. A 25-year intermittent monitoring and a ∼150-year paleolimnological time series from Baptiste Lake, Alberta, were analyzed using a combination of trend, correlation, and multivariate analyses. The temporal overlap between the monitoring and paleolimnological time series provides an opportunity to assess coherence between the data sources. Diatom assemblages in the sediment core show that eutrophic conditions were present for at least 150 years. Monitored water chemistry data since the early 1980s show that total Kjeldahl nitrogen (TKN) has increased by approximately 50% since the early 1990s, whereas concentrations of total phosphorus (TP) have remained stable. Further, measured TKN is significantly correlated to measurements of chlorophyll a over the monitoring period and to diatom-inferred TKN values, suggesting nitrogen limitation in Baptiste Lake. In contrast, measured TP was not correlated to chlorophyll a or diatom-inferred TP. Changes in land use over the past 100 years is the most parsimonious explanation for the nutrient changes. No statistical support for climatic change as a linear predictor of nutrient dynamics was found. Our contemporary and paleolimnological analysis provides an important perspective on the timing and magnitude of nutrient dynamics over ∼150 years. Future government and community decisions on Baptiste Lake management would benefit from testing nutrient limitation and detailed modeling of nutrient runoff from the watershed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".