Tree rings provide early warning signals of jack pine mortality across a moisture gradient in the southern boreal forest
Bibliographic record
Abstract
Recent declines in productivity and tree survival have been widely observed in boreal forests.We used early warning signals (EWS) in tree ring data to anticipate premature mortality in jack pine (Pinus banksiana)-an extensive and dominant species occurring across the moisture-limited southern boreal forest in North America.We sampled tree rings from 113 living and 84 dead trees in three soil moisture regimes (subxeric, submesic, subhygric) in central Saskatchewan, Canada.We reconstructed annual increments of tree basal area to investigate (1) whether we could detect EWS related to mortality of individual trees, and (2) how water availability and tree growth history may explain the mortality warning signs.EWS were evident as punctuated changes in growth patterns prior to transition to an alternative state of reduced growth before dying.This transition was likely triggered by a combination of severe drought and insect outbreak.Higher moisture availability associated with a soil moisture gradient did not appear to reduce tree sensitivity to stress-induced mortality.Our results suggest tree rings offer considerable potential for detecting critical transitions in tree growth, which are linked to premature mortality.
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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".