Pros and cons of group living in the forest tent caterpillar: separating the roles of silk and of grouping
Bibliographic record
Abstract
Abstract Group living can incur both benefits and costs, mediated by different mechanisms. In many gregarious caterpillars, collective use of a network of silk trails is thought to improve foraging. Grouping, i.e., close contact with conspecifics, has been postulated to have both positive (thermoregulation and predator defense) and negative (competition and pathogen transmission) effects. The present experiment distinguishes between silk produced by group members and grouping per se in their effects on growth and development of both early and late larval stadia of the forest tent caterpillar [ Malacosoma disstria Hübner (Lepidoptera: Lasiocampidae)] in a laboratory context. For both developmental stadia tested, pre‐established silk trails decreased latency to food finding and hence increased food consumption and growth rate. For younger larvae, pre‐established silk also decreased investment in silk production. Grouping young caterpillars accelerated development at the expense of growth, possibly as a mechanism to avoid intraspecific competition in later larval stadia. In older caterpillars, grouping decreased meal duration, suggesting that competition can indeed occur towards the end of larval development, even in the presence of surplus food. This led to a decrease in growth without any effect on instar duration. The benefits of exogenous silk thus decreased during larval development, whereas the costs associated with crowding increased. Ontogenetic shifts in grouping are common in many taxa: the present study is among the first to provide empirical evidence for an adaptive explanation of observed ontogenetic changes in aggregative behavior.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".