Eutrophication forcings on a peri-urban lake ecosystem: Context for integrated watershed to airshed management
Bibliographic record
Abstract
Peri-urban lakes increasingly experience intensified anthropogenic impacts as watershed uses and developments increase. Cultus Lake is an oligo-mesotrophic, peri-urban lake near Vancouver, British Columbia, Canada that experiences significant seasonal tourism, anthropogenic nutrient loadings, and associated cultural eutrophication. Left unabated, these cumulative stresses threaten the critical habitat and persistence of two endemic species at risk (Coastrange Sculpin, Cultus population; Cultus Lake sockeye salmon) and diverse lake-derived ecosystem services. We constructed water and nutrient budgets for the Cultus Lake watershed to identify and quantify major sources and loadings of nitrogen (N) and phosphorus (P). A steady-state water quality model, calibrated against current loadings and limnological data, was used to reconstruct the historic lake trophic status and explore limnological changes in response to realistic development and mitigation scenarios. Significant local P loadings to Cultus Lake arise from septic leaching (19%) and migratory gull guano deposition (22%). Watershed runoff contributes the majority of total P (53%) and N (73%) loads to Cultus Lake, with substantial local N contributions arising from the agricultural Columbia Valley (41% of total N load). However, we estimate that up to 66% of N and 70% of P in watershed runoff is ultimately sourced via deposition from the nutrient-contaminated regional airshed, with direct atmospheric deposition on the lake surface contributing an additional 17% of N and 5% of P. Thus, atmospheric deposition is the largest single source of nutrient loading to Cultus Lake, cumulatively responsible for 63% and 42% of total N and P loadings, respectively. Modeled future loading scenarios suggest Cultus Lake could become mesotrophic within the next 25 years, highlighting a heightened need for near-term abatement of P loads. Although mitigating P loads from local watershed sources will slow the rate of eutrophication, management efforts targeting reductions in atmospheric-P within the regional airshed are necessary to halt or reverse lake eutrophication, and conserve both critical habitat for imperiled species at risk and lake-derived ecosystem services.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".