Divergent impacts of experimental lake-level drawdown on planktonic and benthic plant communities in a boreal forest lake
Bibliographic record
Abstract
Water-surface elevation in lake 226 (L226) of the Experimental Lakes Area in northwestern Ontario, Canada, was lowered experimentally by 23 m during each of three successive winters, and increased naturally but incompletely during the ensuing summers. Our objective was to compare the responses of the littoral and pelagic plant communities to this physical disturbance. Water-chemistry changes were muted, and neither nitrogen nor phosphorus concentration changed. Phytoplankton biomass, species assemblages, productivity, and nutrient status were largely unaffected except for small changes in species diversity and relative abundance of cyanobacteria and cryptophytes. Despite possible transient changes in functional and structural properties, the principal disruption for benthic algae was loss of colonizable surfaces. Floating-leaved and submersed macrophytes (hydrophytes) responded initially with large decreases in biomass and cover. The subsequent response of hydrophytes to drawdown varied: relative frequency of isoetids such as Eriocaulon septangulare decreased, while that of pondweeds such as Potamogeton spirillus increased. The trophic impacts of declining lake levels, whether due to hydroelectric reservoir manipulations or climate change, are likely to be much greater in the littoral zone than in the pelagic zone if major nutrients are unaltered.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".