Climatic influences on wood anatomy and tree‐ring features of Great Basin conifers at a new mountain observatory
Bibliographic record
Abstract
PREMISE OF THE STUDY: A network of mountain observing stations has been installed in the Great Basin of North America. NevCAN (Nevada Climate-ecohydrological Assessment Network), which spans a latitudinal range of 2.5° and two elevation ranges of about 2000 m each, enabled us to investigate tree growth in relation to climate. • METHODS: We analyzed wood anatomy and tree-ring characteristics of four conifer species in response to different levels of water availability by comparing a low- and a high-elevation population. Chronologies of earlywood and latewood widths, as well as cellular parameters, were developed from the year 2000 to 2012. • RESULTS: At the southern (drier and warmer) sites, Pinus monophylla had smaller cell lumen, tracheid diameter, and cell wall thickness. Pinus monophylla and P. flexilis showed bigger cellular elements at the higher elevations, whereas the opposite pattern was found in Picea engelmannii and Pinus longaeva. When all species and sites were pooled together, stem diameter was positively related with earlywood anatomical parameters. • DISCUSSION: We have provided a glimpse of the applications that NevCAN, as a new scientific tool, could allow in the general field of botany. In particular, we were able to investigate how differences in water stress related to elevation lead to changes in xylem anatomy.
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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 | 0.000 | 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".