Rare Vascular Plants in the Lake Simcoe Watershed: Planning, Prediction and Protection
Bibliographic record
Abstract
Using the threat-status ranks for vascular plants found through Vegetation Sampling Protocol surveys within the Lake Simcoe watershed, this research looks at the protection of Vulnerable (S3) and Imperiled (S2) vascular plants within municipal planning zones and policy and planning documents. As well, several variables were tested to determine what can be used to predict the presence of rare plants. Land use maps revealed for Innisfil, Newmarket, Oro-Medonte and Barrie that 250.7 ha of Natural Heritage Features containing S2 and S3 plants are designated for protection, while 655.6 ha are being converted to development or open space. Protection zoning within these municipalities was shown to contain 969.5 ha of development and open space, which does not necessarily serve conservation goals. A series of t-Tests produced statistically insignificant results for Natural Heritage Feature size (P-value 0.99), Floristic Quality Index (P-value 0.92) and biomass (P-value 0.48) as indicators in predicting the presence of rare plants. Furthermore, land use within a 1 km radius around sites with rare plants and randomly selected non-rare plant containing sites, yielded one statistically interesting result from a stepwise logistic regression; Agriculture and Lawn produced a P-value of 0.09, with higher levels being associated with rare plants. This may be due to the rural landscape containing more natural areas. It can be concluded that vegetation surveys need to continue in order to uncover rare plants. In conjunction with locating these species, protection policy and planning documents should expand and solidify their inclusion of rare vascular plants, if hope is to remain for rare plant continuity, or possible decrease in rarity.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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".