Recruitment patterns and growth of high-elevation pines in response to climatic variability (1883–2013), in the western Great Basin, USA
Bibliographic record
Abstract
Over the period 1883–2013, recruitment of subalpine limber pine (Pinus flexilis E. James) and Great Basin bristlecone pine (Pinus longaeva D.K. Bailey) above the upper tree line, below the lower tree line, and across middle-elevation forest borders occurred at localized sites across four mountain ranges in the western Great Basin. A synchronous pulse at all ecotones occurred between 1963 and 2000 (limber pine) and between 1955 and 1978 (bristlecone pine) when pines expanded 225 m beyond forest borders. Little recruitment occurred before this interval or in the 21st century. No obvious environmental factors distinguished recruitment locations from nonrecruitment locations. Where their ranges overlap, limber pine has leapfrogged above bristlecone pine by 300 m. Limber pine tree-ring chronologies, developed to compare radial-growth responses with recruitment, showed dominant pulses of increased growth during the same interval as recruitment. Significant climate correlations of growth and recruitment indicated lead and lag effects as much as 6 years and complex relationships with climate variables, corroborating the importance of cumulative climate effects relative to any single year. Water relations were the most important drivers of growth and recruitment and interacted with growing-season minimum and maximum temperatures. These results underscore the importance of studying ecotones at all margins when evaluating conifer response to climate change.
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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".