Relative Abundance and Functional Role of Whitebark Pine at Treeline in the Northern Rocky Mountains
Bibliographic record
Abstract
Facilitative interactions among plant species enable plant community development under stressful environmental conditions. Previous studies in two treeline communities within the alpine-treeline ecotone on the Rocky Mountain Front in northwestern Montana, U.S.A., indicated that whitebark pine (Pinus albicaulis) serves as the majority tree island initiator, thus facilitating the development of tree islands (Resler and Tomback, 2008). However, 33.7% of whitebark pine at these treeline study sites were infected by the introduced pathogen Cronartium ribicola, which causes white pine blister rust. We examined the prevalence of whitebark pine, its ecological role, and the incidence of blister rust within two study sites, Tibbs Butte and Wyoming Creek, to the south on the Beartooth Plateau, and within two study sites, Stanley Glacier and Gibbon Pass, to the north in Kootenay and Banff National Parks, for comparison with information from the Rocky Mountain Front (Resler and Tomback, 2008). We found that whitebark pine was an important component of treeline communities in both the southern and northern study areas, although its abundance and ecological role varied with study site. Nearly half the solitary trees sampled overall in the northern and southern study areas were whitebark pine. Whitebark pine was also the most frequently occurring conifer species among tree islands at three of the four study sites. Across all study sites, whitebark pine served as tree island initiator for 29.4% of the tree islands sampled, but was a more frequent initiator within two study sites. Blister rust incidence for the Wyoming Creek study site in the southern study area was 7.7%, and for the Stanley Glacier study site in the northern study area, 16.2%. Damage and mortality over time from Cronartium ribicola will diminish the current ecological role of whitebark pine as a facilitator of landscape vegetation pattern development and may confound predictions of upward movement of treeline in response to climate warming.
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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 | 0.000 |
| 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".