Economic Consequences of Insect Pests Outbreaks in Boreal Forests: A Literature Review
Bibliographic record
Abstract
Outbreaks of pests are considered one of the most destructive types of natural forest disorders. In recent years the severity of such outbreaks has rapidly increased due to the process of global warming, which affects the rate of reproduction of pests and the range of their natural distribution. Economic consequences of these types of disturbances are of particular importance. Though many studies have been conducted in the field of tree phytophages ecology, the issues of estimating economic damage and the formation of mechanisms for its minimization have been poorly studied. This article presents a review of studies on the problem of the harmful effects of forest pests classified by their localization. The area of study includes mainly boreal forests located in a number of European countries, the USA, Canada and Russia. Our study reviews the range of instruments applied to prevent disturbances mentioned above and mitigate corresponding negative consequences. Despite the fact that there are theoretical approaches to the analysis of the economic consequences of forest damage by pests, they still cannot find practical application
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".