Water level thresholds of benthic macroinvertebrate richness, structure, and function of boreal lake stony littoral habitats
Bibliographic record
Abstract
We investigated the role of water level fluctuation on benthic macroinvertebrate communities of stony littoral habitats located in the Boreal Shield Ecozone. Using the reference condition approach (RCA), regression analysis, nonmetric multidimensional scaling (NMDS), and analysis of variance (ANOVA), we analyzed the benthic macroinvertebrate community structure of 20 natural lakes and 28 hydroelectric reservoirs to determine if they are structured by change in water level (amplitude). Along a gradient of amplitude intensity, we found that taxa richness decreases with increasing amplitude (r2 = 0.47–0.60). Littoral benthic macroinvertebrate community structure is significantly different in reservoirs that experience amplitudes > 2.0 m. Out of 28 reservoirs, 13 fell outside the 95.5% confidence ellipse determined by 20 reference lakes. Functional mobility group and functional feeding group composition are also altered with increasing amplitude (nonparametric ANOVA, P < 0.05). Further, a change in benthic macroinvertebrate functional composition occurs after a change in taxa richness. Interestingly, reservoirs that experienced amplitudes < 2.0 m had benthic macroinvertebrate communities whose structural and functional composition is similar to lakes experiencing natural water level fluctuations.
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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 | 0.000 |
| Science and technology studies | 0.000 | 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".