The potential for invertebratevertebrate intraguild predation: the predatory relationship between wolf spiders (<i>Gladicosa pulchra</i>) and ground skinks (<i>Scincella lateralis</i>)
Bibliographic record
Abstract
Intraguild predation is described as predation among organisms that exploit similar resources. As wolf spiders (Araneae, Lycosidae) are generalist predators that share habitat and food resources with the ground skink Scincella lateralis, we conducted a series of laboratory experiments to determine if wolf spiders are capable of preying upon ground skinks. Wolf spiders (Gladicosa pulchra) successfully preyed on skinks during 3 of 20 encounters, but did not overtly respond to chemical stimuli from the skinks. Skinks employed antipredatory behaviors (i.e., immobility) when exposed to visual and chemical stimuli from spiders, providing evidence that they recognize spiders as predators prior to an encounter. In an additional experiment, the hypothesis that increased skink movement would lead to an increase in spider attacks was tested. Skinks exhibited high levels of movement in this experiment, with spider predation occurring during 4 of 10 encounters. The presence of structural refugia played a significant role in this predatorprey interaction by increasing the amount of time required for a spider to prey upon a skink. Our results indicate that G. pulchra can prey upon S. lateralis, and that skinks may recognize cues deposited on the substrate by spiders. These data indicate that these two species may interact in an ecologically meaningful manner.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".