Influence of Host Tree Condition on the Performance of<i>Tetropium fuscum</i>(Coleoptera: Cerambycidae)
Bibliographic record
Abstract
Tetropium fuscum (F.) attacks weakened Norway spruce, Picea abies (L.) Karst., in its native Europe and may colonize healthy spruce in Nova Scotia, Canada. We used manipulative field experiments to evaluate: 1) the development of T. fuscum on apparently healthy red spruce (Picea rubens Sarg.) in Nova Scotia; 2) the influence of red spruce physiological condition (healthy, girdled or cut) on T. fuscum performance; and 3) the impact of natural enemies and competitors on T. fuscum performance when developing on trees of varying condition. Tetropium fuscum successfully developed on healthy red spruce. Survival was higher on healthy than on girdled or cut trees when larvae were exposed to natural enemies and competitors. The benefits of reduced competition and parasitism on healthy trees appeared to compensate for any reductions in nutritional quality, increase in host resistance, or both. In contrast, when T. fuscum were protected from natural enemies, apparent survival was highest on girdled trees. Tetropium fuscum development took longer on healthy than on cut or girdled trees, and emerged adults were largest on healthy trees. The disparities in adult sizes among the three treatments may mean that healthy trees are more nutritious. Alternatively, the differences may indicate that a greater amount of time was spent feeding in healthy than in girdled or cut trees. Tree condition appears to have a direct impact on the success of T. fuscum, influencing survival, development time, and adult size, and may mediate the impact of natural enemies and competitors, further affecting T. fuscum performance.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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; both teacher heads agree on what is shown here.
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".