Biodiversity assessment of riparian areas, upper Cornwallis River and tributaries
Bibliographic record
Abstract
The Annapolis Valley, Nova Scotia, Canada has a long history of agricultural use and has experienced an intensification of farming practices during the last century. Agricultural land use patterns have contributed to the accumulation of pollutants in the Cornwallis River and the loss of regional biodiversity. Riparian areas filter water, trap sediment and provide habitat for a variety of wildlife. We explored the relationship between terrestrial biodiversity, land use and agricultural practices along riparian areas in the Tri-brook Watershed of the upper Cornwallis River. We identified 17 study sites in four different biotopes in riparian areas. Birds and terrestrial invertebrates were sampled as indicator taxa to assess terrestrial biodiversity. A point count bird survey was conducted in June and terrestrial invertebrates were collected in pit fall traps in July. We also completed a Riparian Health Assessment (RHA) at each study site and a plot- : based vegetation survey. There were 113 individual birds found within our study sites representing 17 different species. We captured 1540 carabid beetles from 24 species. Using correspondence analysis and regression models we determined a significant relationship among forest cover, bird diversity and the RHA. There was a significant negative relationship between carabid richness and RHA. Declining grassland birds were found at sites which were classified as unhealthy by the RHA. Involvement of farmers and landowners in the development of a watershed stakeholder group must be considered essential in the management of agricultural riparian zones and the enhancement of habitat for terrestrial wildlife.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| 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".