Evaluating the diversity, distribution patterns and habitat preferences of Carex species (Cyperaceae) in western Canada using geospatial analysis
Bibliographic record
Abstract
Sedge ( Carex ) is a highly diversified genus of vascular plants with high species diversity in cold-temperate areas of the Northern Hemisphere. In Canada, 313 species of Carex are documented with 105 species in Saskatchewan, making it the largest genus of vascular plants in this Province. Research on the distribution and ecology of sedges in Saskatchewan is extremely limited. This study aims to find the distribution patterns of Carex species and identify their habitat preferences relative to environmental conditions in Saskatchewan through the application of GIS spatial analysis tools. Data on specimen-based occurrences of Carex species were collected, validated and consolidated from the Flora of Saskatchewan Association (FOSA) and analysed along with Carex datasets mobilised by the Global Biodiversity Information Facility (GBIF), resulting in 2655 individual records of occurrences. Our research includes seven environmental variables to explore relationships between Carex species and environment. The study produced comprehensive spatial maps and graphs illustrating species occurrences, species richness and diversity hotspots. It was found that Carex species have a diverse habitat preference strongly associated with temperature and precipitation and, to a lesser extent, soils. The species occurrences are mostly concentrated in the Boreal Plain and Prairie ecozones of the Province. Notably, species richness peaked in the central part of Saskatchewan in areas with moderate elevation and temperature and high precipitation. This integrative analysis emphasises the need for region-specific assessments to effectively manage and preserve biodiversity.
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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 | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".