Host plant phenology drives risky larval dispersal in an outbreaking insect defoliator
Bibliographic record
Abstract
Abstract Dispersal away from natal sites allows individuals to find suitable foraging sites to complete their development and successfully reproduce. Drivers of risky dispersal behaviour in forest landscapes by young larvae of outbreaking defoliators are not well understood. We assessed dispersal behaviour of young spruce budworm larvae in relation to spring budburst phenology of primary and secondary hosts, balsam fir and black spruce, respectively. We tested whether tree species and presence of suitable feeding sites influenced dispersal away from source branches and subsequent redistribution of insects. Laboratory experiments showed that dispersal is an active behaviour during which larvae disperse away from source trees without open buds, regardless of species. Establishment on sink branches was highest when they possessed open buds and the source did not. In the field, larval dispersal was higher from black spruce than from balsam fir and larval establishment was more persistent on balsam fir. The decision to disperse occurs before budburst of either host species. Larvae disperse preferentially away from black spruce whose old needles are too tough for larval mining, compared to balsam fir that can be mined for sustenance and refuge while larvae await budburst. While black spruce is a suitable host species after its buds expand, phenological defences drive larval dispersal away from this host plant. These findings are the first to show how risky dispersal behaviour in larval Lepidoptera is facultative and is determined by local food availability.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".