Response of aspen to a warming climate along a latitudinal gradient in the Rocky Mountains, USA
Bibliographic record
Abstract
The 21st century’s warming climate threatens aspen ( Populus tremuloides) growth in the southern Rocky Mountains (western US), endangering ecosystem diversity, functionality, and associated services. This study linked aspen growth with temperature and moisture variations, assessing how warmer climates and seasonal changes affect ring widths. Sampling 211 aspen trees from 12 latitudinally distributed sites, we compiled three regional aspen chronologies spanning 1913–2018. We investigated climate-growth associations using correlation and modeling ( climwin) techniques. Results revealed that aspen at the trailing southern edge of the Rocky Mountains are vulnerable to drought, where elevated temperatures and diminished precipitation emerge as primary factors contributing to their reduced growth. In contrast, aspens in the northern region of the gradient exhibited a positive growth response to rising temperatures, potentially linked to the alleviation of growth-limiting cold temperatures. However, while pre-2000s droughts increased growth, recent droughts elicited growth reductions in the North; suggesting that with continued warming, northern populations will increasingly face sensitivity to droughts akin to their southern counterparts. These findings emphasize the increased vulnerability of southern Rocky Mountain aspen populations to climate change-induced growth constraints, particularly in the anticipated warmer and drier conditions of the 21st century. This study is crucial to understanding aspen responses to climate fluctuations in the region.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".