No evidence of recent (1995–2013) decrease of yellow-cedar in Alaska
Bibliographic record
Abstract
Climate change is expected to impact forests worldwide, and yellow-cedar (Callitropsis nootkatensis (D. Don) Oerst. ex D.P. Little) decline has been used as an example of how changing climate can impact a tree species. However, most previous research has not placed yellow-cedar decline within the context of yellow-cedar overall. We used a 2004–2013 regional inventory of the temperate rainforest of Alaska (671 plots with yellow-cedar) to estimate current attributes and a subset of 564 remeasured plots (established 1995–1998) to estimate recent change. Results show that in unmanaged forests, yellow-cedar live tree basal area recently (1995–1998 to 2004–2013) increased, with a 95% confidence interval of a 0.3% to 3.3% increase per decade. Yellow-cedar has a relatively low mortality rate, 0.41% of trees per year. An analysis of live tree to snag ratios was consistent with elevated mortality of yellow-cedar prior to 1995 but also indicated that little range contraction had occurred. The large numbers and wide geographic range of yellow-cedar trees in Alaska and the recent (1995–2013) stability in the monitored population serve as important contextual information for yellow-cedar decline. This research also illustrates that understanding the spatial and temporal complexities of how tree species respond to climate change will be improved if focused studies are accompanied by regional monitoring.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".