Comparative responses of phytoplankton during chemical recovery in atmospherically and experimentally acidified lakes<sup>1</sup>
Bibliographic record
Abstract
Twenty lakes recovering from a century of atmospheric acid deposition over Northeastern Ontario were resurveyed for phytoplankton following a 20‐year period and were compared with a 23‐year study of an experimentally acidified lake, L302S (Experimental Lakes Area, ON, Canada). Phytoplankton species significantly tracked abiotic changes during both acidification and chemical recovery in all lakes based on concordance testing. However, ordination analyses showed that many phytoplankton communities had not returned to their preacidification state. Significant explanatory variables of taxonomic responses were pH, dissolved organic carbon (DOC), and inorganic nutrients (N, P), based on canonical correspondence analysis (CCA). Increases in DOC and pH influenced a significant taxonomic shift from acid‐tolerant dinoflagellates to a diverse assemblage of cyanobacteria, chlorophytes, and diatoms. Declining nitrogen levels defined a secondary environmental gradient, which was characterized by a decrease in filamentous green algal abundance. L302S remained remote in ordination space from the more chronically and heavily polluted lakes in Northeastern Ontario, indicating that experimental acidification provided a conservative estimate of the true damage to atmospherically polluted lakes. However, L302S did increasingly resemble lakes in Northeastern Ontario, suggesting that experimental acidification simulated the impacts of moderate levels of atmospheric pollution. Our findings demonstrate the importance of ecological history in understanding the responses by boreal lake ecosystems to environmental change.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".