Cross-scale Drivers of Natural Disturbances Prone to Anthropogenic Amplification: The Dynamics of Bark Beetle Eruptions
Bibliographic record
Abstract
Biome-scale disturbances by eruptive herbivores provide valuable insights into species interactions, ecosystem function, and impacts of global change. We present a conceptual framework using one system as a model, emphasizing interactions across levels of biological hierarchy and spatiotemporal scales. Bark beetles are major natural disturbance agents in western North American forests. However, recent bark beetle population eruptions have exceeded the frequencies, impacts, and ranges documented during the previous 125 years. Extensive host abundance and susceptibility, concentrated beetle density, favorable weather, optimal symbiotic associations, and escape from natural enemies must occur jointly for beetles to surpass a series of thresholds and exert widespread disturbance. Opposing feedbacks determine qualitatively distinct outcomes at junctures at the biochemical through landscape levels. Eruptions occur when key thresholds are surpassed, prior constraints cease to exert influence, and positive feedbacks amplify across scales. These dynamics are bidirectional, as landscape features influence how lower-scale processes are amplified or buffered. Climate change and reduced habitat heterogeneity increase the likelihood that key thresholds will be exceeded, and may cause fundamental regime shifts. Systems in which endogenous feedbacks can dominate after external forces foster the initial breach of thresholds appear particularly sensitive to anthropogenic perturbations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".