Breeding matters: Natal experience influences population state-dependent host acceptance by an eruptive insect herbivore
Bibliographic record
Abstract
Eruptive forest insects are highly influential agents of change in forest ecosystems, and their effects have increased with recent climate change. State-dependent life histories contribute significantly to the population dynamics of eruptive forest insect herbivores; however, the proximate mechanisms by which these species shift between states is poorly understood. Laboratory bioassays were conducted using the mountain pine beetle (Dendroctonus ponderosae) to determine the effect of maternal host selection on offspring host preferences, as they apply to population state-dependent behaviors. Female mountain pine beetles exhibited state-dependent preference for artificial host material amended with monoterpenes in the absence of other cues, such that individuals reared in high-density epidemic-state simulations rejected low monoterpene conditions, while low-density endemic-state beetles accepted low monoterpene conditions. State-specific behavior in offspring was dependent on rearing conditions, as a function of maternal host selection, and these effects were observed within one generation. Density-dependent host selection behaviors exhibited by female mountain pine beetle offspring is reinforced by context-dependent maternal effects arising from parental host selection, and in situ exposure to conspecifics. These results demonstrate potential proximate mechanisms that control population dynamics in eruptive forest insects, and will allow for more accurate predictions of continued impact and spread of these species.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| 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 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".