Habitat may limit herb migration at the northern edge of the Appalachian deciduous forest *This paper is dedicated to our botanical mentor, the late Dr. Sam P. Vander Kloet.
Bibliographic record
Abstract
Forest herbs account for greater species richness than any other plant type in deciduous forests and are the most vulnerable to anthropogenic disturbances. We examined whether the limited distribution of rare Appalachian forest herbs in Nova Scotia is related to edaphic specialization or a history of anthropogenic disturbance. Remnant populations are restricted to floodplain forest, where both habitat factors and disturbance history differ significantly from those of adjacent upland sugar maple forest. Contrasting soil and litter layers between floodplain stands and adjacent upland sites revealed the latter to be deficient in key cations (calcium, magnesium, boron); however, regression models for uplands and for floodplains showed that native herb richness was related to soil fertility in each case. Soil calcium accounted for most of the species richness variation among floodplains for native herbs and for a large seeded guild that contains most of the rare species on floodplains. Given the widespread anthropogenic decalcification of forest soils throughout eastern North America, conservation efforts must (i) increase and connect deciduous forest floodplain ecosystems and (ii) understand how to manage and create suitable cation-rich migration corridors in the forest landscape.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".