Temporary thinning shock in previously shaded red spruce
Bibliographic record
Abstract
Silvicultural thinning can lead to rapid microclimatic changes for residual trees. Despite the benefits of decreased competition, thinning may induce “thinning shock”—temporary negative physiological responses as trees acclimate to new conditions. We examined the impact of thinning on the microclimate and physiology of residual, previously shaded red spruce ( Picea rubens Sarg.) trees relative to non-thinned controls. Both daily maximum temperature and vapor pressure deficit increased post thinning, with larger increases observed on hotter and drier days. In response to these environmental changes, we found clear evidence of physiological declines. At 1.7 weeks post thinning, we found a 0.59 MPa reduction in average midday water potential relative to control trees, which lasted for an additional 1.4 weeks. Thus, the trees in the thinning treatment were at or beyond published estimates of needle turgor loss. Thinning decreased the photosynthetic efficiency of current-year needles by 3.8% after 2 weeks, and it declined by 1.3% per week for the remainder of the growing season. These results suggest that thinning shock occurs in red spruce, a shade-adapted, climate-sensitive species. Thinning shock may contribute to the lagged growth responses commonly observed post thinning, and these effects may be more extreme in novel future climates.
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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 | 0.000 | 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".