Evaluation of funnel traps for estimating tree mortality and associated population phase of spruce beetle in Utah
Bibliographic record
Abstract
Although funnel traps are routinely used to manage bark beetles, little is known regarding the relationship between trap captures and tree mortality near the trap. We conducted a 4 year study in Utah to examine the correlation between funnel-trap captures of spruce beetle (Dendroctonus rufipennis Kirby) and mortality of Engelmann spruce (Picea engelmannii Parry ex Engelm.) within a 10 ha block of the trap. Using recursive partitioning tree analyses, rules were developed for predicting spruce mortality and associated levels of beetle population phase (endemic or epidemic), in the current year and subsequent year, for a given level of trap captures. Although model predictions of infested-stem counts had large variances, our results suggest that funnel-trap captures can be reliably used to estimate relative levels of tree mortality, expressed as spruce beetle population phase. Classification-tree analyses indicate that captures of ~842 spruce beetles during a season (late May to mid-August) from a single funnel trap represent a threshold between endemic (<2 mass-attacked stems/ha) and epidemic conditions (≥2 mass-attacked stems/ha) for either the current or the subsequent year relative to deployment of the funnel trap. Likewise, a lack of infested hosts within 10 m of a funnel trap, also known as spillover, was associated with endemic conditions, whereas trees attacked near the trap correlated with epidemic conditions.
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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 | 0.006 | 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 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".