Relative potential for stand persistence of riparian and upland aspen stands of a semi-arid montane landscape of the Southern Rocky Mountains
Bibliographic record
Abstract
Several studies have predicted a loss of quaking aspen ( Populus tremuloides) from many western landscapes, but other studies have suggested that aspen persistence is driven by local site factors. Increased frequency of acute drought has been implicated as an important factor driving overstory mortality and reduced regeneration densities in the region. We investigated the relationship between aspen regeneration and site moisture availability potential using ecosystem type as a proxy. We hypothesized that aspen stands growing along perennial-flowing streams would support higher aspen regeneration densities than upland aspen stands. We compared stand structure, groundcover composition, and regeneration densities of nine riparian aspen stands with nine paired upland aspen stands in the Caribou–Targhee National Forest. Aspen regeneration densities were significantly higher in the riparian aspen stands (845.3 + 318.7 stems ha−1) compared to the upland aspen stands (249.1 + 74.1 stems ha−1) for regeneration shorter than 1 m ( p = 0.0391). Riparian stands also exhibited significantly higher forb ( p < 0.001) and graminoid ( p < 0.001) cover compared to upland aspen stands, suggesting that riparian sites provided higher site moisture availability. We suggest that riparian areas may provide refugia for aspen in the future considering projections of increased incidence of acute drought.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".