Littoral benthic macroinvertebrates under contrasting drawdown in a reservoir and a natural lake
Bibliographic record
Abstract
Littoral benthic macroinvertebrate communities in lake reservoirs often are exposed to repeated fluctuations in water level, but little is known of the effects of drawdown on benthic community composition. We compared the taxonomic composition and spatial patterns of benthic macroinvertebrate communities in sediments of littoral areas in a reservoir with >30 y of seasonal drawdowns (Sooke Lake Reservoir [SLR]) and a natural lake with little seasonal change in water levels (Shawnigan Lake [SHL]). Contrary to our predictions, macroinvertebrate density and biomass usually were greater in SLR than in SHL. In SLR, densities and biomasses of macroinvertebrates, especially chironomids, were higher below the drawdown exposure zone than in the upper littoral area. Chironomids with r-selected survival strategies (i.e., smaller size) or desiccant-resistant stages appeared well suited to the fluctuating environment of littoral zones in reservoirs. Orthocladiinae, Chironomini, Tanytarsini, and Tanypodinae dominated at sampling sites immediately below the drawdown exposure zone in SLR, whereas only Orthocladiinae dominated at deeper sites. Warm water from an expanded epilimnion apparently extended the distribution of Diamesinae farther from shore in SLR than in SHL. Chironomini generally were the dominant macroinvertebrate taxon in SHL, and the relative biomass of Diamesinae increased with depth. Distributions of oligochaetes and nematodes extended farther from shore in SLR than in SHL. These contrasting benthic macroinvertebrate communities indicate that variable drawdown regimes could have significant impacts on benthic food webs and the transfer of energy and nutrients to the pelagic area.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".