Temperature Mediates Shifts in Individual Aggressiveness, Activity Level, and Social Behavior in a Spider
Bibliographic record
Abstract
Although in recent years behavioral syndromes have received a wealth of attention, how traits within syndromes respond to changing environments is not well resolved. Here, we test the effects of temperature on a suite of behavioral traits in the spider Anelosimus studiosus to determine (1) whether there are shifts in individuals’ social tendency, activity level, and foraging behavior in response to temperature, (2) if these traits shift are in the direction predicted by within-population axes of trait covariance, and (3) whether the effects of temperature differ among individuals. In previous work, we documented a behavioral syndrome in A. studiosus where increased tolerance of conspecifics is correlated with decreased activity level and aggressiveness toward prey. Furthermore, there are distinct among-population differences in behavior, where individuals from warm sites tend to be more aggressive and active than individuals from cold sites. Our data here reveal that at warmer temperatures A. studiosus exhibit diminished tolerance of conspecifics, increased activity levels, shorter latencies of attack, and increased tendencies to attack multiple prey items. Furthermore, we found that individual differences in behavior were consistent across temperature regimes for the majority of behavioral traits considered here: social tendency, activity level, and latency of attack. These findings are consistent with the hypothesis that these behaviors are linked together by shared genetic underpinnings (e.g., metabolic differences) and shift non-independently in response to contemporary abiotic environment (i.e., temperature). Furthermore, our data suggest that temperature itself could be responsible for the among-population variation in social structure in A. studiosus.
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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".