Biology and establishment of mountain shrubs on mining disturbances in the Rocky Mountains, USA
Bibliographic record
Abstract
Abstract The Rocky Mountains of the western United States contain many economically important natural resources. Increasing development of these resources has lead to land degradation, which often requires restoration efforts. A common type of disturbance in this region is mineral extraction and these activities often occur in zones of vegetation dominated by shrubs. These mined lands have proven to be particularly challenging to restore to native shrub cover. Mountain shrubland species such as big sagebrush (Artemisia tridentata), antelope bitterbrush (Purshia tridentata), Saskatoon serviceberry (Amelanchier alnifolia), black chokecherry (Prunus virginiana), mountain mahogany (Cercocarpus montanus), and snowberry (Symphoricarpos sp.) are crucial species for wildlife in this region due to the seasonal dependence of many wildlife species on the mountain shrubland zones. The development of successful restoration techniques for these key shrub species is therefore important for the continued and sustainable utilization of natural resources in the Rocky Mountains. The purpose of this literature review is to provide a reference to land managers working on woody plant establishment on mining disturbances in mountain shrublands in the Rocky Mountains. This review covers the biology, ecology, and propagation of six shrub species that are of primary importance for meeting regulatory compliance in this region. Based upon this survey of the published literature, we conclude that successful establishment of these species has most often involved: (1) utilization of local shrub ecotypes, varieties or subspecies in reclamation efforts, (2) protection from browsing during the establishment phase, (3) strategies for avoiding herbaceous competition, and (4) providing a source of mutualistic soil organisms. Additional specific recommendations for each of these species are discussed. Copyright © 2003 John Wiley & Sons, Ltd.
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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 | 0.000 | 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".