Interannual Variation of Benthic Macroinvertebrate Communities at Long-Term Monitoring Sites Impacted by Human Activities: Implications for Bioassessment
Bibliographic record
Abstract
Bioassessment assumes that ecological conditions remain stable in the absence of environmental changes. Evidence suggests this assumption may hold for reference streams, but knowledge gaps remain for impacted streams. Our study quantified interannual variation of benthic macroinvertebrate communities, monitored for at least 14 years in eight impacted streams in the Upper Thames River watershed in Ontario, Canada. Benthic communities exhibited moderate interannual variation in relative abundance of EPT (Ephemeroptera, Plecoptera and Trichoptera) and Chironomidae taxa. Year-to-year changes were reflected in lower community persistence than that observed in studies of reference streams. In contrast, tolerance-based metrics showed minimal interannual variation, suggesting compositional changes were because of taxonomic substitutions, in which one tolerant taxon replaced another. Analyses indicated limited directionality in temporal variation for most bioassessment metrics. An exception was taxa richness, which increased at most sites, possibly because of changes in subsampling. However, no associations between calculated bioassessment metrics and measured environmental factors (stream flow and water chemistry) or sampling procedures were observed. We conclude interannual variation in ecological conditions can be substantial and may not be associated with deterministic factors routinely measured in stream assessments. We recommend increased sampling frequency and traits-based assessment as options for limiting effects of interannual variation on assessment results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".