Influence of climate on the growth of quaking aspen (<i>Populus tremuloides</i>) in Colorado and southern Wyoming
Bibliographic record
Abstract
We analyzed a series of increment cores collected from 260 adult dominant or co-dominant quaking aspen (Populus tremuloides Michx.) trees from national forests across Colorado and southern Wyoming in 2009 and 2010. Half of the cores were collected from trees in stands with a high amount of crown dieback, and half were from lightly damaged stands. We define the level of stand damage based on stand survey data in which lightly damaged stands had average crown dieback of 16% and heavily damaged stands averaged 41%. Upon analysis, two-thirds of the cores collected did not exhibit radial growth correlated with region-wide patterns (e.g., climate) and were classified as having a low cohesive response. The site variable most predictive of whether a stand exhibited high cohesive response or low cohesive response was site elevation, followed by aspect, slope, and canopy closure. Sites with high cohesive response stands were more likely to have aspen bark beetle damage, white rot, and Cryptosphaeria canker. We did not detect relationships between tree growth and summer precipitation from 1900–2008, but there was a relationship between growth and annual precipitation. A growth model included maximum May and July temperatures, as well as the current and previous year’s annual precipitation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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 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".