Rare Plants of Southern Alberta: Examining the community dynamics and co-occurrence patterns of Asclepias viridiflora and Geranium viscosissimum
Bibliographic record
Abstract
Conservation needs a greater focus on how rare species interact within their neighborhoods. Rare plants have been found to exist in communities that are positively associated (have plants that facilitate or help one another). Rare plants often rely on facilitation for their persistence; however, the mechanisms of facilitation are understudied. One example of facilitation occurs through shared pollinators. Common plants may attract numerous pollinators to a community, and as a result, the rare plants who rely on those pollinators for their reproduction will benefit indirectly from those common plants. Although studies have examined how pollinators can facilitate indirect relationships with other plants, few works have addressed how rare plants may benefit from pollination facilitation that does not involve co-flowering, such as sequential mutualism. This work aims to address these gaps by examining the pollinator-mediated plant interactions of two rare species in southern Alberta: Asclepias viridiflora (Green Comet Milkweed), and Geranium viscosissimum (Sticky Purple Geranium). These species are medicinally and culturally significant to people's of the Nitsitaapi (Blackfoot) Confederacy. Asclepias viridiflora is known as Onnikiisaikimsskaan in Blackfoot. The study involves collaboration with elder William Singer III (Api'soomaahka) of the Kainai First Nation and uses data from community science platforms such as iNaturalist to address the research questions.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".