Mortality and Growth of Residual Whitebark Pine in High Elevation Variable Retention Harvest Sites in Southeastern British Columbia
Bibliographic record
Abstract
The rapid decline of whitebark pine (Pinus albicaulis) throughout its range is a pressing conservation issue. This keystone species endures multiple pressures toward local extirpation including forest health agents, forest succession, and climate change. Currently, silviculture practices are categorized as a stand-level strategy aimed at effective whitebark pine restoration/conservation. In this thesis I retrospectively evaluated the mortality and growth of whitebark pine at five low-retention ESSF silviculture treatments located in southeastern British Columbia, Canada. I found that whitebark pine reserve trees in low retention silviculture prescriptions were prone to elevated post-harvest mortality due to windthrow within the initial five-year post-harvest interval. Post-harvest growth rates indicated that mature reserve trees were likely to demonstrate increased radial growth after disturbance and that pre-harvest growth rates due to suspected forest health agents can minimize these increases. A two sample Welch t-test found no significant difference between the resistance index of control and reserve trees one year after harvest in three of the four sites examined, suggesting that radial growth reduction was negligible for surviving trees. Visual examination of the post-harvest reserve tree chronologies, however, showed a common two to three-year growth lag. Reserve trees indicated a significant difference in the recovery period for the harvest event year with a one-year lag in two of the four sites. However, this result was confounded by the following: (1) one of the sites showed a negative radial growth trend pre-harvest; and, (2) a pointer year analysis identified an inflated growth response in the control trees for the same year for the second site. These growth-climate relationships indicated that whitebark pine tree chronologies in closed-canopy forests were energy-limited systems with a significant negative correlation to July SPEI.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".