Collective behavior and colony persistence of social spiders depends on their physical environment
Bibliographic record
Abstract
The physical environment occupied by group-living animals can profoundly affect their cooperative social interactions and therefore their collective behavior and success. These effects can be especially apparent in human-modified habitats, which often harbor substantial variation in the physical environments available within them. For nest-building animal societies, this influence of the physical environment on collective behavior can be mediated by the construction of nests—nests could either buffer animal behavior from changes in the physical environment or facilitate shifts in behavior through changes in nest structure. We test these alternative hypotheses by examining the differences in collective prey-attacking behavior and colony persistence between fence-dwelling and tree-dwelling colonies of Stegodyphus dumicola social spiders. Fences and trees represent substantially different physical environments: fences are 2-dimensional and relatively homogenous environments, whereas tree branches are 3-dimensional and relatively heterogeneous. We found that fence-dwelling colonies attack prey more quickly and with more attackers than tree-dwelling colonies in both field and controlled settings. Moreover, in the field, fence-dwelling colonies captured more prey, were more likely to persist, and had a greater number of individuals remaining at the end of the experiment than tree-dwelling colonies. Intriguingly, we also observed a greater propensity for colony fragmentation in tree-dwelling colonies than fence-dwelling colonies. Our results demonstrate that the physical environment is an important influence on the collective behavior and persistence of colonies of social spiders, and suggest multiple possible proximate and ultimate mechanisms—including variation in web complexity, dispersal behavior, and bet-hedging—by which this influence may be realized.
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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 | 0.001 |
| 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 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".