Whole-lake algal responses to a century of acidic industrial deposition on the Canadian Shield
Bibliographic record
Abstract
A century of cultural acidification is hypothesized to have altered algal community structure in boreal lakes. To date, this hypothesis has remained untested because of both the lack of data predating the onset of industrial pollution and incomplete estimates of whole-lake algal community structure. High-pressure liquid chromatography (HPLC) of sedimentary pigments was used to quantify whole-lake algal responses to acid deposition in six boreal lakes located in Killarney Park, Ontario, Canada. Concomitant significant increases in chlorophyll and carotenoid concentrations, diatom-inferred lake acidity, and metal levels since 1900 suggested that algal abundances in four acidified lakes and one small, circumneutral lake were enhanced by aerial pollution. An alternate explanation is that increased acidity and underwater light availability in the acidified lakes shifted algal abundance towards phytobenthos and deepwater phytoplankton, whose pigment signatures were better preserved in the sediments. Taxonomically diagnostic pigment stratigraphies were consistent with shifts in algal community structure towards filamentous green phytobenthos and deepwater phytoflagellates in the acidified lakes. Our findings suggest that decades of aerial pollution have altered the base of foodwebs in boreal lakes, potentially rendering them less resilient to other environmental stressors.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".