Impact of Forest Fragmentation on Patterns of Mountain Pine Beetle-Caused Tree Mortality
Bibliographic record
Abstract
The current outbreak of mountain pine beetle, Dendroctonus ponderosae Hopkins, has led to extensive tree mortality in British Columbia and the western United States. While the greatest impacts of the outbreak have been in British Columbia, ongoing impacts are expected as the outbreak continues to spread eastward towards Canada’s boreal and eastern pine forests. Successful mitigation of this outbreak is dependent on understanding how the beetle’s host selection behaviour is influenced by the patchwork of tree mortality across the landscape. While several studies have shown that selective mechanisms operate at the individual tree level, less attention has been given to beetles’ preference for variation in spatial forest patterns, namely forest fragmentation, and if such preference changes with changing population conditions. The objective of this study is to explore the influence of fragmentation on the location of mountain pine beetle caused mortality. Using a negative binomial regression model, we tested the significance of a fragmentation measure called the Aggregation Index for predicting beetle-caused tree mortality in the central interior of British Columbia, Canada in 2000 and 2005. The results explain that mountain pine beetle OPEN ACCESS Forests 2013, 4 280 exhibit a density-dependent dynamic behaviour related to forest patterns, with fragmented forests experiencing greater tree mortality when beetle populations are low (2000). Conversely, more contiguous forests are preferred when populations reach epidemic levels (2005). These results reinforce existing findings that bark beetles exhibit a strong host configuration preference at low population levels and that such pressures are relaxed when beetle densities are high.
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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) | 0.005 | 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".