Low Non-structural Carbon Accumulation in Spring Reduces Growth and Increases Mortality in Conifers Defoliated by Spruce Budworm
Bibliographic record
Abstract
Spruce budworm (Choristoneura fumiferana) outbreaks are important disturbance events in the boreal forests of northeastern North America, causing major growth loss and widespread tree mortality. The physiological mechanisms leading to tree mortality remain poorly understood and two important functional traits, tree-ring width and concentration of stored carbohydrate, can serve as indicators of tree vitality during defoliation. This study aims to test the hypothesis that storage starch is an indicator of tree vitality by (1) exploring the link among reductions in storage, growth and mortality, and (2) identifying starch or sugar threshold to predict the risk of mortality. We use balsam fir and black spruce, two main host species of spruce budworm. We sampled 81 trees across seven experimental sites in eastern Quebec, Canada, and assessed defoliation intensity, tree-ring growth, and tree vitality. Soluble sugar and starch concentrations in needles, twigs, and roots were measured from spring to autumn. Under conditions of increased defoliation, carbon allocation to reserves and radial growth decreased in a similar manner for both species. Starch concentration within twigs and needles in May and June was the best indicator of carbon status in defoliated trees. We observed the highest reductions in growth two to 3 years prior to mortality concurrently with reductions in starch in May and June. When starch concentrations were lower than 28 mgg -1 dw in needles, the probability of balsam fir mortality exceeded 50%. At this level of starch, reserves and newly produced carbon are insufficient to support tree growth and vitality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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 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".