Growth responses of subalpine fir to climatic variability in the Pacific Northwest
Bibliographic record
Abstract
We studied regional variation in growth-limiting factors and responses to climatic variability in subalpine forests by analyzing growth patterns for 28 tree-ring growth chronologies from subalpine fir (Abies lasiocarpa (Hook.) Nutt.) stands in the Cascade and Olympic Mountains (Washington and Oregon, U.S.A.). Factor analysis identified four distinct time series of common growth patterns; the dominant growth pattern at any site varied with annual precipitation and temperature (elevation). Throughout much of the region, growth is negatively correlated with winter precipitation and spring snowpack depth, indicating that growth is limited primarily by short growing seasons. On the driest and warmest sites, growth is negatively correlated with previous summer temperature, suggesting that low summer soil moisture limits growth. Growth patterns in two regions were sensitive to climatic variability associated with the Pacific Decadal Oscillation, apparently responding to low-frequency variation in spring snowpack and summer soil moisture (one negatively, one positively). This regional-scale analysis shows that subalpine fir growth in the Cascades and Olympics is limited by different climatic factors in different subregional climates. Climategrowth relationships are similar to those for a co-occurring species, mountain hemlock (Tsuga mertensiana (Bong.) Carrière), suggesting broad biogeographic patterns of response to climatic variability and change by subalpine forest ecosystems in the Pacific Northwest.
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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 | 0.001 |
| 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".