Tree‐ring isotopes reveal drought sensitivity in trees killed by spruce beetle outbreaks in south‐central Alaska
Bibliographic record
Abstract
Abstract Increasing temperatures have resulted in reduced growth and increased tree mortality across large areas of western North American forests. We use tree‐ring isotope chronologies (δ 13 C and δ 18 O) from live and dead trees from four locations in south‐central Alaska, USA, to test whether white spruce trees killed by recent spruce beetle ( Dendroctonus rufipennis Kirby) outbreaks showed evidence of drought stress prior to death. Trees that were killed were more sensitive to spring/summer temperature and/or precipitation than trees that survived. At two of our sites, we found greater correlations between the δ 13 C and δ 18 O chronologies and spring/summer temperatures in dead trees than in live trees, suggesting that trees that are more sensitive to temperature‐induced drought stress are more likely to be killed. At one site, the difference between δ 13 C in live and dead trees was related to winter/spring precipitation, with dead trees showing stronger correlations between δ 13 C and precipitation, again suggesting increased water stress in dead trees. At all sites where δ 18 O was measured, δ 18 O chronologies showed the greatest difference in climate response between live and dead groups, with δ 18 O in live trees correlating more strongly with late winter precipitation than dead trees. Our results indicate that sites where trees are already sensitive to warm or dry early growing‐season conditions experienced the most beetle‐kill, which has important implications for forecasting future mortality events in Alaska.
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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 | 0.001 | 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".