Dispersal behaviour as the outcome and trigger of multilevel selection in a social spider
Bibliographic record
Abstract
Abstract The facultatively social spider Anelosimus studiosus offers a unique opportunity for understanding how multilevel selection acts in natural populations. However, the importance of previous empirical studies are shaded by a conceptual debate about whether colony-level selection is truly present in these populations or not. Here we introduce a detailed individual based model, where practically all assumptions are supported by empirical data. The only element of the female A. studiosus life cycle missing from the literature is how maturing female spiders decide whether to disperse. This behavioural component we estimate with evolutionary simulations. This model is able to recapitulate the characteristic size and composition distributions of natural populations in different environments. The evolutionary simulations revealed that the optimal dispersal behaviour of a maturing female varies both with her ecological environment and behavioural phenotype. This finding is open for straightforward empirical testing. In agreement with empirical findings we have established parameter ranges where the population is prone to extinction without multiple-female nests. We propose that the dispersal behaviour of individuals is both the result and the prerequisite of multilevel selection in this species.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".