Improving Mountain Pine Beetle Survival Predictions Using Multi-Year Temperatures Across the Western USA
Bibliographic record
Abstract
Global climate change has led to an increase in large-scale bark beetle outbreaks in forests around the world, resulting in significant impacts to forest ecosystems, timber economies, and forest-dependent communities. As such, prediction models that utilize temperature for estimating future bark beetle locations and consequential tree mortality are critical for informing forest management decision-making in an attempt to mitigate and adapt to pending and current outbreaks. This is especially true for physiological models that account for the effects of overwinter temperatures on bark beetle survival, as seasonal temperatures, specifically during winter months, exert the greatest impact on bark beetle mortality during various stages of life cycle development. Yet, how temperature observations are used to predict bark beetle survival can significantly under- or over-estimate the role that temperature variability plays in annual tree mortality, especially under current climate change trajectories. This study evaluates how representations of winter temperature influence bark beetle survival estimates. Using the recent outbreak of mountain pine beetle (Dendroctonus ponderosae Hopkins) across the western USA as a case study, single-year to decade-long winter temperature averages were used as inputs into a physiological beetle survival prediction model, the results of which were compared against beetle-induced tree mortality observations using temporal autoregressive models. Results show that using longer-term survival averages of seven to ten years significantly increases the likelihood that temperature alone can predict general levels of beetle survival and hence beetle-induced mortality. These findings demonstrate the importance of considering the role of long-term temperature observations when forecasting bark beetle outbreaks, and that year-to-year temperature variability may be constrained in predicting beetle survival during outbreak periods.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".