Impacts of agriculture, riparian zone health, and land use type on water quality in a Kings County, Nova Scotia stream
Bibliographic record
Abstract
Streams and rivers in the Annapolis Valley, Nova Scotia are greatly degraded. The assumption is that this degradation is largely due to farming practices. The purpose of this study was to determine the relationship between land use, specifically agriculture, and water quality. The differences in water quality immediately upstream and downstream of two individual farms and adjacent tributaries in the Fisher Brook Watershed of Kings County, N.S. were examined and compared to two reference sites and sites along the Cornwallis River upstream, at the confluence, and downstream from where the Fisher Brook meets the Cornwallis River. Nitrate, ammonia, total nitrogen, orthophosphate, total phosphorus, fecal coliform, chlorophyll a, and particulate organic matter were measured. Correlations were drawn between water quality and riparian zone health and watershed land use fractions. It was shown that each parameter was generally low in the reference sites, with the exception of particulate organic matter as measured by loss-on-ignition. Water quality variables generally had higher values downstream from farms than upstream and farmland sample sites generally had higher values than reference sites. There seemed to be a positive correlation between water quality and fraction of natural stand vegetation and a negative correlation between water quality and fraction of agriculture in the watershed. Increasing riparian zone health was significantly correlated with a decrease in water quality. A negligible effect on the Cornwallis River was observed from the Fisher Brook tributaries.
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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.001 | 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".