Habitat, dispersal, and distribution of the rare Orange-fruit Horsegentian (<i>Triosteum aurantiacum</i> E.P. Bicknell; Caprifoliaceae) in northern Nova Scotia, Canada
Bibliographic record
Abstract
Why some plant species are rare and how rare species persist are foundational questions in community ecology. In 2015 we repeated a 2006 survey of three river valleys in rural Antigonish County, northern Nova Scotia, Canada, which support populations of the rare herb Orange-fruit Horse-gentian (Triosteum aurantiacum E.P. Bicknell) to see how the populations had changed over a decade and to learn more about why the plant remains rare. Our survey confirms previous observations that Orange-fruit Horse-gentian is largely restricted to the understorey of hardwood and mixedwood stands, on bare ground within and near river floodplains, often with White Ash (Fraxinus americana L.). Predictive maps based on geographic information system modelling led to the discovery of new occurrences of the species along the three original rivers and along a fourth river, including a dense cluster in mature hardwood forest, which had not previously been considered habitat. Measurements of photosynthetic capacity using pulse-amplitude modulation (PAM) fluorometry showed significant stress on horse-gentian plants growing in full sunlight or light shade compared with plants beneath closed canopy confirming this plant is shade-adapted. Late-autumn observations of potential consumers of horse-gentian fruit suggest that White-tailed Deer (Odocoileus virginianus) may be the primary long-range disperser of seeds. Hence, this species may remain rare in northern Nova Scotia because its optimal habitat (mature, closed-canopy forest with open understorey and calcium-rich soil) is rare and distributed in disjunct patches (mostly along floodplains) and seed dispersal is limited by the range size of the deer.
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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 | 0.001 | 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".