Ethanol accumulation during severe drought may signal tree vulnerability to detection and attack by bark beetles
Bibliographic record
Abstract
Tree mortality from temperature-driven drought is occurring in forests around the world, often in conjunction with bark beetle outbreaks when carbon allocation to tree defense declines. Physiological metrics for detecting stressed trees with enhanced vulnerability prior to bark beetle attacks remain elusive. Ethanol, water, monoterpene concentrations, and composition were examined in the phloem and sapwood of drought-stressed Aleppo pine (Pinus halepensis Mill.) freshly attacked by mature Mediterranean pine shoot beetles (Tomicus destruens (Wollaston, 1865)) and in neighboring unattacked trees. The attacked trees were more water-stressed and contained, on average, 2.1 and 2.4 times more ethanol in the phloem and sapwood, respectively, than the neighboring attack-free trees. This response is consistent with the known attraction of T. destruens to ethanol. Most monoterpene concentrations in the phloem, but not sapwood, were greater in tissues of attacked trees, whereas compositional differences were minor between the two tree groups for both tissues. Tissue water content explained much of the variation in phloem monoterpene concentrations, which increased as water in the phloem declined, suggesting that higher constitutive quantities existed in the more stressed trees prior to the attacks. Monoterpenes may have contributed to host tree selection by T. destruens, but their potential influence is considered less important than that of ethanol based on beetle responses to these compounds in previous trapping studies. This is the first report of elevated ethanol concentrations in tissues of trees experiencing natural drought stress and suggests that ethanol measurements in severely water-stressed trees may allow early detection of those most vulnerable to bark beetle attack.
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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 | 0.002 | 0.000 |
| 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 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".