Firewood Transport as a Vector of Forest Pest Dispersal in North America: A Scoping Review
Bibliographic record
Abstract
Native and nonnative insects and diseases can result in detrimental impacts to trees and forests, including the loss of economic resources and ecosystem services. Increases in globalization and changing human behaviors have created new anthropogenic pathways for long distance pest dispersal. In North America, literature suggests that once a forest or tree pest is established, the movement of firewood by the general public for recreational or home heating purposes is one of the primary pathways for its dispersal. Understanding human perceptions and behaviors is essential to inform the most effective strategies for modifying firewood and pest dispersal by humans. This scoping review seeks to assess trends and gaps in the existing literature, as well as patterns in behavior related to forest pest dispersal through firewood movement in North America. We identified 76 documents that addressed this topic to which we applied inclusion and exclusion criteria to select articles for further analysis. Twenty-five articles met the inclusion criteria and were categorized based on five identified themes: 1) insect incidence in firewood, 2) insect dispersal via firewood, 3) recreational firewood movement, 4) firewood treatments, and 5) behavior and rule compliance. The selected articles show trends that suggest that firewood movement presents a risk for forest insect dispersal, but that behavior can be modified, and compliance, monitoring, and treatments should be strengthened. This scoping review found limited research about western United States, Mexico, and Canada, various insect species and other organisms, regulation and management, awareness, and behavioral dimensions of firewood movement.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".