Forest mortality in high-elevation whitebark pine (<i>Pinus albicaulis</i>) forests of eastern California, USA; influence of environmental context, bark beetles, climatic water deficit, and warming
Bibliographic record
Abstract
Whitebark pine ( Pinus albicaulis Engelm.) in subalpine zones of eastern California experienced significant mortality from 2007 to 2010. Dying stands were dense (mean basal area 47.5 m 2 /ha), young (mean 176 years), and even-age; mean stand mortality was 70%. Stands were at low elevations (mean 2993 m), on northerly aspects, and experienced warmer, drier climates relative to the regional species distribution. White pine blister rust was not observed; mountain pine beetle infestations were extensive. Ring widths were negatively correlated with climatic water deficit and positively correlated with water-year precipitation. Although trees that survived had greater growth during the 20th century than trees that died, in the 19th century trees that eventually died grew better than trees that survived, suggesting selection for genetic adaptation to current climates as a result of differential tree mortality. Air surveys (2006–2010) in the Sierra Nevada, Mt. Shasta, and Warner Mountains showed similar trends to the intensive studies. Observed mortality from air surveys was highest in the Warner Mountains (38%) and lowest in the Sierra Nevada (5%); northern aspects at lower elevations within each mountain region had the highest probabilities of mortality and dying stands had higher climatic water deficit. Scenarios for the future of whitebark pine in California are discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".