Floristic similarity, diversity and endemism as indicators of refugia characteristics and needs in the West
Bibliographic record
Abstract
The floras of mountain ranges, and their similarity, beta diversity and endemism, are indicative of processes of community assembly; they are also the initial conditions for coming disassembly and reassembly in response to climate change. As such, these characteristics can inform thinking on refugia. The published floras or approximations for 42 mountain ranges in the three major mountain systems (Sierra-Cascades, Rocky Mountains and Great Basin ranges) across the western USA and southwestern Canada were analysed. The similarity is higher among the ranges of the Rockies while equally low among the ranges of the Sierra-Cascades and Great Basin. Mantel correlations of similarity with geographic distance are also higher for the Rocky Mountains. Endemism is relatively high, but is highest in the Sierra-Cascades (due to the Sierra Nevada as the single largest range) and lowest in the Great Basin, where assemblages are allochthonous. These differences indicate that the geologic substrates of the Cascade volcanoes, which are much younger than any others, play a role in addition to geographic isolation in community assembly. The pattern of similarity and endemism indicates that the ranges of the Cascades will not function well as stepping stones and the endemic species that they harbor may need more protection than those of the Rocky Mountains. The geometry of the ranges is complemented by geology in setting the stage for similarity and the potential for refugia across the West. Understanding the geographic template as initial conditions for the future can guide the forecast of refugia and related monitoring or protection efforts.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".