The frequency of leg autotomy and its influence on survival in natural populations of the wolf spider <i>Pardosa valens</i>
Bibliographic record
Abstract
Autotomy occurs when an animal intentionally sacrifices an appendage to escape predation or free a limb. While immediately beneficial, loss of an appendage can lead to a variety of future costs. In many spiders, leg autotomy is common; previous work has sometimes demonstrated autotomy costs in some behaviors, while other times, no costs of autotomy occur. We examined frequency of autotomy in two riparian zone populations of the wolf spider Pardosa valens Barnes, 1959 and then used both mark–recapture work at these sites and laboratory predation trials to determine whether autotomy affected survival. Autotomy occurred in 31% of spiders; males were more likely than females to have a missing leg, but female reproductive status (carrying an egg sac or not) was unrelated to leg loss status. At both sites, survival over 1 week in the field was significantly higher for intact spiders than for spiders missing a leg, for both sexes and both female reproductive states. Additionally, when we paired intact and autotomized spiders with a predator (the larger wolf spider Rabidosa santrita (Chamberlin & Ivie, 1942)), autotomized spiders were more likely to be attacked and eaten. Our results suggest that leg autotomy in P. valens leads to a significant future survival cost, and we discuss how this cost may affect males and females differently.
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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 | 0.001 |
| 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".