Macroecology and Potential Drivers of Diversity in Webspinner Maternal Care (Order Embioptera)
Bibliographic record
Abstract
Abstract Embioptera display variability in egg-handling as part of their defense against natural enemies. Because species living in tropical regions experience potentially higher risks of predation than those in temperate climes, we hypothesized that variable risk might explain this variability. We used actual evapotranspiration (AET) rates as a stand-in for climate, region, and potential interactions with natural enemies. We predicted that more complex investments, such as coating individual eggs, organizing them, and topping the cluster with thick silk would co-occur with greater predation threats in tropical regions, scored as higher AET. We predicted that simpler organization of eggs would occur where predator risk would be lower, as in temperate regions (lower AET). We used phylogenetic comparative methods to assess whether more complex egg handling behavior correlated with high AET scores. We quantified five traits of egg handling from field and laboratory evidence for 29 species from habitats ranging from low to high AET. Initial pGLS and pGLM analyses showed a weak effect of AET on parental care index. Upon exclusion of three exotic species spread artificially by trade and collected outside their native ranges, we found strong effects of predation threat in both pGLS and pGLM analyses. These analyses revealed that species that experience potentially greater predation threats exhibited behaviors that corresponded to more complex handling and organization of eggs by the mother. These results align nicely with analyses that also detected that additional lines of defense of eggs typify the behavior of tropical species of other primitively social arthropods.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".