Forest developmental trajectories in mountain pine beetle disturbed forests of Rocky Mountain National Park, Colorado
Bibliographic record
Abstract
A mountain pine beetle (Dendroctonus ponderosae Hopkins) epidemic has caused widespread mortality of lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) trees across western North America,. We characterized the initial effects of beetle-induced mortality on forest structure and composition in Rocky Mountain National Park, Colorado. In 2008, we surveyed stand structure and tree species composition across lodgepole pine dominated forests in the western portion of the Park. We defined five lodgepole pine forest types to describe variability in pre-epidemic forest conditions. This forested landscape appears to be resilient to the effects of the beetle. Surviving trees, including both canopy trees and saplings, were plentiful in most of the post-epidemic forests, even after accounting for anticipated future mortality. Subalpine fir (Abies lasiocarpa (Hook.) Nutt.), Engelmann spruce (Picea engelmannii Parry ex Engelm.), and aspen (Populus tremuloides Michx.) had modestly higher relative abundances after the epidemic. Lodgepole pine remained the dominant species on approximately 85% of the landscape. The impact of the outbreak on forest structure and composition varied considerably among the five forest types, suggesting that post-epidemic forest developmental trajectories will vary according to pre-outbreak stand characteristics. Active management efforts to regenerate lodgepole pine forests, e.g., tree planting, will likely not be necessary on this landscape.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".