Effects of livestock grazing on aquatic macroinvertebrates in Southern Interior wetlands of British Columbia, Canada
Bibliographic record
Abstract
Grasslands in the southern interior of British Columbia are extensively grazed by free ranging livestock. Water sources are limited in these grassland landscapes and wetlands are commonly used by livestock for drinking water and forage. My study examined the impacts of livestock disturbance on the abundance, biomass and community composition of aquatic macroinvertebrates residing in these wetlands. Aquatic macroinvertebrates were collected in the spring and summer of 2008 from 17 wetlands with a range of grazing disturbance. Three sweep and core samples were collected from each wetland and grazing intensity was determined by the amount of bare ground at each site. Spring sweep total abundance (r2=0.464, p=0.003) and biomass (r2=0.728, p<0.001) were negatively correlated with livestock disturbance as were spring abundance and biomass of zygopterans (r2=0.593, p<0.001; adj. r2=0.513, p=0.001). Spring sweep family richness (r2=0.462, p=0.003), Shannon’s family diversity (r2=0.569, p<0.001) and Simpson’s family diversity (r2=0.385, p=0.008) also decreased as livestock disturbance increased. Resource managers should consider Zygoptera (damselflies) as a potential indicator of wetland water quality and livestock impact. Range plans should adopt only light grazing in wetland areas and limit livestock access to sustain the biodiversity and productivity of these valuable aquatic ecosystems.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".