TREE MORTALITY FOLLOWING PARTIAL HARVESTS IS DETERMINED BY SKIDDING PROXIMITY
Bibliographic record
Abstract
Recently developed structural retention harvesting strategies aim to improve habitat and ecological services provided by managed forest stands by better emulating natural disturbances. The potential for elevated mortality of residual trees following such harvests remains a critical concern for forest managers, and may present a barrier to more widespread implementation of the approach. We used a harvest chronosequence combined with dendrochronological techniques and an individual-based neighborhood analysis to examine the rate and time course of residual-tree mortality in the first decade following operational partial "structural retention" harvests in the boreal forest of Ontario, Canada. In the first year after harvest, residual-tree mortality peaked at 12.6 times the preharvest rate. Subsequently, mortality declined rapidly and approached preharvest levels within 10 years. Proximity to skid trails was the most important predictor both of windthrow and standing death, which contributed roughly equally to total postharvest mortality. Local exposure further increased windthrow risk, while crowding enhanced the risk of standing mortality. Ten years after harvest, an average of 10.5% of residual trees had died as a result of elevated postharvest mortality. Predicted cumulative elevated mortality in the first decade after harvest ranged from 2.4% to 37% of residual trees across the observed gradient of skid trail proximity, indicating that postharvest mortality will remain at or below acceptable rates only if skidding impacts are minimized. These results represent an important step toward understanding how elevated mortality may influence stand dynamics and habitat supply following moderate-severity disturbances such as partial harvests, insect outbreaks, and windstorms.
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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 | 0.000 | 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) | 0.002 | 0.002 |
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; both teacher heads agree on what is shown here.
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".