Assessment of Littoral Benthic Invertebrate Communities at the Land–Water Interface in Lakes Recovering from Severe Acid- and Metal-Damage
Bibliographic record
Abstract
Benthic invertebrate communities within confluence sites, or areas of sediment deposition, are shaped by the input of catchment products including coarse woody debris, organic and inorganic particulates, and contaminants, but these sites also appear to be potential “hotspots” where recolonization of severely damaged ecosystems begins. Two species of leaf packs and a sweep netting technique were used to assess benthic invertebrate communities across a gradient of 14 confluence sites in 3 recovering lakes near the copper and nickel smelters in Sudbury, Canada. Environmental variables including delta habitat composition, delta area and length, and composition of deposited materials were used to detect spatial patterns in littoral benthic invertebrate communities. Benthic invertebrate community relationships with water chemistry were also assessed. Partial redundancy analysis (pRDA) showed that all sampling methods detected similar gradients of increasing invertebrate community richness and diversity as area and length of the sediment delta and the surface organic matter abundance increased. Two-way nested ANOVAs showed significant differences (p < .05) in taxa richness and diversity metrics among sites. Of the three methods, the benthic invertebrate community measurements from the birch leaf packs provided the strongest correlations with measures of organic matter inputs or habitat characteristics of the confluence zones. These correlations suggest that tree planting in riparian areas, or organic matter or macrophyte additions to littoral zones, may enhance littoral benthic invertebrate richness and diversity in acid and metal damaged lakes.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".