Foraging behavior and extended phenotype independently affect foraging success in spiders
Bibliographic record
Abstract
Abstract Multiple phenotypic traits often interact with each other to determine an individual’s fitness. Behavioral and extended phenotypic traits, such as architectural constructions, can contribute to fitness in an integrated way. The goal of this study was to understand how the interaction between behavioral and extended phenotypic traits can affect foraging success. We tested this question using black widow spiders, where spiders that are aggressive in a foraging context tend to build more gumfooted silk lines that aid in prey capture, while non-aggressive spiders build webs with fewer gumfooted lines. We repeatedly assessed behavior and web structure to quantify relationships between these traits, and then allowed spiders to forage for live prey on their own web or the web of a conspecific that differed in structure. Thus, we assessed how varying combinations of behavior and web structure affect foraging success, and if correlational selection might act on them. We confirmed that aggressiveness and number of gumfooted lines are positively correlated and found that capture success increased with both aggressiveness and the number of gumfooted lines. Yet, we did not find any evidence for correlational selection: aggressiveness and number of gumfooted lines appeared to affect foraging success independently of each other. These findings highlight that a correlation between traits that contribute towards the same ecological function does not necessarily imply correlational selection. Taking advantage of the experimental convenience afforded by extended phenotypic traits can provide insight into the functional consequences of phenotypic variation within and between individuals.
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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 | 0.000 | 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) | 0.000 | 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".