Twentieth-century warming and the dendroclimatology of declining yellow-cedar forests in southeastern Alaska
Bibliographic record
Abstract
Decline of yellow-cedar ( Chamaecyparis nootkatensis ((D. Don) Spach) has occurred on 200 000 ha of temperate rainforests across southeastern Alaska. Because declining forests appeared soon after the Little Ice Age and are limited mostly to low elevations (whereas higher elevation forests remain healthy), recent studies have hypothesized a climatic mechanism involving early dehardening, reduced snowpack, and freezing injury. This hypothesis assumes that a specific suite of microclimatic conditions occurs during late winter and declining cedar populations across the region have responded similarly to these conditions. Based on the first geographically extensive tree ring chronologies constructed for southeastern Alaska, we tested these assumptions by investigating regional climatic trends and the growth responses of declining cedar populations to this climatic variation. Warming winter trends were observed for southeastern Alaska, resulting in potentially injurious conditions for yellow-cedar due to reduced snowfall and frequent occurrence of severe thaw–freeze events. Declining cedar forests shared a common regional chronology for which late-winter weather was the best predictor of annual growth of surviving trees. Overall, our findings verify the influence of elevational gradients of temperature and snow cover on exposure to climatic stressors, support the climatic hypothesis across large spatial and temporal scales, and suggest cedar decline may expand with continued warming.
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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) | 0.001 | 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".