Effects of phenological synchronization on caterpillar early-instar survival under a changing climate
Bibliographic record
Abstract
Early-instar caterpillars experience very high and often very variable mortality; if it is density dependent, it can be a key factor in outbreak dynamics. Plant physical and chemical defenses can be extremely effective against young caterpillars, even of specialists. Phenological asynchrony with host plants can lead to dispersal and mortality in the early instars and increased predation or poor nutrition in later instars. Predation on early-instar larvae (including cannibalism) can be extremely high, parasitism appears generally low, and pathogens acquired early in larval development can lead to high mortality in later stadia. Four well-studied species reveal very different roles of early-instar mortality in population dynamics. In spruce budworm and gypsy moth, early-instar mortality rates can be very high; they do not drive outbreak cycles because density dependence is weak, but can modulate cycles and contribute to outbreak size and duration. For the autumnal moth, early-instar survival depends on host plant synchrony, but may or may not be density dependent. For monarch butterflies, the relative importance of larval mortality rates in population dynamics remains unclear. Tritrophic interactions between herbivores, host plants, natural enemies, and microbes play complex and species-specific roles in early-instar ecology, leading to emergent dynamics in population fluctuations. The phenology of these relationships is often poorly understood, making their responses to climate change unpredictable.
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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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".